fix: default to 125 GiB GPU memory on 128 GiB nodes

README.md

@@ -161,7 +161,7 @@ TF edge defaults to a 180-second upstream I/O timeout, leaving room for the gene
 
 ### GPU memory ceiling on inference nodes
 
-Set `services.omlx.gpu_memory_gb` in `tfconfig.yaml` for a shared ceiling, or override it with `nodes.<node>.runtime.gpu_memory_gb`. Use a positive integer in **GiB**. Omitted node values inherit the service setting; explicit `null` selects actual RAM minus 10 GiB. A 128 GiB node therefore defaults to 118 GiB (`iogpu.wired_limit_mb=120832`). RAM comes from `hw.memsize` on the inference node, not the controller or the inventory's `ram_gb`.
+Set `services.omlx.gpu_memory_gb` in `tfconfig.yaml` for a shared ceiling, or override it with `nodes.<node>.runtime.gpu_memory_gb`. Use a positive integer in **GiB**. Omitted node values inherit the service setting; explicit `null` selects actual RAM minus 3 GiB. A 128 GiB node therefore defaults to 125 GiB (`iogpu.wired_limit_mb=128000`). RAM comes from `hw.memsize` on the inference node, not the controller or the inventory's `ram_gb`.
 
 `make bootstrap <node>`, `make restart <node>`, and sync with runtime restart install the setting in the oMLX system LaunchDaemon. At every start, including after reboot, a short root-owned plist command validates the limit, applies it only when changed, verifies it by reading sysctl back, then uses `sudo -n -H -u <node.user>` to start oMLX as the non-root runtime user. No extra sysctl sudoers permission is granted. An unsupported host, invalid limit, or failed write/readback prevents oMLX startup and reports the error in its stderr log. Dry-run only renders the plist. The legacy user LaunchAgent and process managers do not apply GPU memory settings; use the system `daemon` manager.
 
@@ -220,7 +220,7 @@ Thunder Forge service ports live in `tfconfig.yaml` under `services:`:
 | `services.edge.host` | `0.0.0.0` | TF edge bind address; use `0.0.0.0` for LAN clients, keep raw Olla private |
 | `services.edge.port` | `40116` | Local TF edge OpenAI-compatible proxy |
 | `services.omlx.port` | `8018` | Default oMLX node runtime port when a node runtime omits `port` |
-| `services.omlx.gpu_memory_gb` | `null` | Host-wide GPU wired-memory ceiling in GiB; null/omitted means actual node RAM minus 10 GiB |
+| `services.omlx.gpu_memory_gb` | `null` | Host-wide GPU wired-memory ceiling in GiB; null/omitted means actual node RAM minus 3 GiB |
 | `services.edge.access_log` | `logs/tf-edge-access.jsonl` | TF edge JSONL accounting log |
 | `services.frontend.admin_user` | empty | Admin account used for frontend system-daemon sudo operations |
 

src/thunder_forge/cluster/config.py

@@ -382,7 +382,7 @@ def _parse_gpu_memory_gb(raw: object, *, name: str) -> int | None:
     if raw is None:
         return None
     if type(raw) is not int or raw <= 0:
-        raise ValueError(f"{name} must be a positive integer in GiB or null (RAM minus 10 GiB)")
+        raise ValueError(f"{name} must be a positive integer in GiB or null (RAM minus 3 GiB)")
     return raw
 
 

src/thunder_forge/cluster/omlx.py

@@ -803,7 +803,7 @@ def _gpu_memory_start_script(node: Node, program_arguments: list[str]) -> str:
     if limit is not None and limit * 1024 > 2**63 - 1:
         raise ValueError("gpu_memory_gb exceeds the supported system integer range")
     # GB in tfconfig follows the binary units of hw.memsize and iogpu.wired_limit_mb.
-    target = str(limit * 1024) if limit is not None else "$((total_mb - 10240))"
+    target = str(limit * 1024) if limit is not None else "$((total_mb - 3072))"
     command = shlex.join([
         "/usr/bin/sudo", "-n", "-H", "-u", node.user, "--", "/usr/bin/env",
         f"HOME={node.home_dir}",

tests/test_runtime_install.py

@@ -443,11 +443,14 @@ def fake_ssh_run(user, ip, cmd, *, timeout):
 @pytest.mark.parametrize(
     "configured,total_gib,current_mb,write_failure,readback_bad,expected_mb,success",
     [
-        (None, 128, 0, False, False, 120832, True),
-        (None, 64, 0, False, False, 55296, True),
+        (None, 128, 0, False, False, 128000, True),
+        (None, 128, 128000, False, False, 128000, True),
+        (None, 64, 0, False, False, 62464, True),
         (100, 128, 0, False, False, 102400, True),
         (118, 128, 120832, False, False, 120832, True),
-        (None, 8, 0, False, False, None, False),
+        (None, 8, 0, False, False, 5120, True),
+        (None, 3, 0, False, False, None, False),
+        (None, 2, 0, False, False, None, False),
         (128, 128, 0, False, False, None, False),
         (129, 128, 0, False, False, None, False),
         (118, 128, 0, True, False, 120832, False),

tfconfig.example.yaml

@@ -27,7 +27,7 @@ services:
   omlx:
     port: 8018
     # Host-wide Metal wired-memory ceiling, in GiB (1 GiB = 1024 MiB).
-    # null/omitted: actual node RAM minus 10 GiB, computed at each daemon start.
+    # null/omitted: actual node RAM minus 3 GiB, computed at each daemon start.
     # Applied before oMLX starts by the system LaunchDaemon, including after reboot.
     gpu_memory_gb: null
 
@@ -176,8 +176,8 @@ nodes:
       # Optional oMLX memory guard; omit to preserve saved settings/defaults.
       # memory_guard: balanced  # safe, balanced, aggressive, or quoted "off"
       # memory_guard_gb: 100.5  # custom GB ceiling; enables the guard, overrides the tier
-      # Optional override of services.omlx.gpu_memory_gb; null restores RAM minus 10 GiB.
-      # gpu_memory_gb: 118
+      # Optional override of services.omlx.gpu_memory_gb; null restores RAM minus 3 GiB.
+      # gpu_memory_gb: 125
       trusted_network: true
     models:
       - memory