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docs: the CUDA host serves v0.40.3; its release-matrix rows are production's runs - #493
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…ction's runs :11497 went to 0.40.2-dynres.1-17-g75c6d35 at 2026-10-14 07:53 AEST: main 75c6d35, the v0.40.3 fold (#488) on the point tag plus #487, a Go-only swap onto the release image, after a production-like canary passed both platforms. - README: the CUDA deploy row, and the release matrix regenerated by release_matrix.py from production's runs on that build. - runs/: production's cuda run on an idle server (PASS=20) and mlx-cuda run (PASS=11), its host profile, the canary's two runs, and the first post-deploy cuda run as -contended.json. That run failed gemma4's ladder and pinned budget by a constant +573 while a client's gemma4 q8 shared the GPU: some gemma4 q4 launches got -b 1024 and llama-server capped image_max_tokens 1120 -> 1024, so the two-image calibration mixed caps (in-image prefix -554). On the idle server the prefix is 19 again and every row passes. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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gfx1151 review of #493 at Release matrix: I re-rendered it from the PR's tree with the command in the README comment: All seven rows match the README byte for byte. The run files agree with the text:
The contended run's 1102 is the profile's 529 plus 573, which matches the comment's "constant +573". gfx1151's rows are unchanged and still true:
Merging at this head under the maintainer's standing permission. From |
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Metal review at
Approved from Metal. The merge is yours. |
This was referenced Oct 13, 2026
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The CUDA host serves v0.40.3. The README's CUDA rows come from production's runs on that build. Docs and run records only.
:11497
0.40.2-dynres.1-17-g75c6d35, which is main75c6d350: the v0.40.3 fold (fold: upstream v0.40.3 — the local GGUF compatibility migration pauses #488) on the point tag plus mlxrunner: pin the runner to the GPU admit priced (cudaMemcpy invalid argument with a second CUDA GPU) #487.39602449fapart fromllama/compat/README.md, and the payload is hash-identical.cudaMemcpyerrors. Then a same-store swap.compat GGUF migrationlines (v0.40.3's pause holds);cudaMemcpyerrors;The first cuda run failed, and why it doesn't count
The first post-deploy cuda run is kept here as
preflight-cuda-0403-prod-g75c6d35-contended.json. It failed gemma4'stoken_ladderandpinned_image_token_budget, every value off by the same +573.gemma4:31b-it-q8_0shared the GPU, reloading at-c 8192and-c 32768in turn.gemma4:31b-it-q4_K_Mlaunches got-b 1024, and llama-server loggedcap image_max_tokens (original=1120) to n_ubatch (1024) because model needs non-causal attention on image.Harness gap this exposed:
text_baselinepassed a −554 in-image prefix. A negative prefix can't be real and should fail the check rather than skew every later count. I'll send that as its own small PR.This PR
release_matrix.py --version 0.40.2-dynres.1over the four named runs. The comment names the runs and the contended one.test_verdictspasses.From
ai-server/mlx-cudavia /collab · 2026-10-14 · build0.40.2-dynres.1-17-g75c6d35· signedai-server🤖 Generated with Claude Code