docs: add Mistral Medium 3.5 VLM coverage and fine-tuning guide#2091
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docs: add Mistral Medium 3.5 VLM coverage and fine-tuning guide#2091
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Mistral AI's new flagship 128B dense VLM is now supported in NeMo AutoModel via the Mistral3FP8VLMForConditionalGeneration custom class (Pixtral vision tower + Ministral-3 dense decoder, FP8 on disk). Mistral Medium 3.5 merges Mistral Medium 3.1, Magistral Medium, and Devstral 2 into a single checkpoint with a configurable reasoning mode and a 256k context window — open-weights under a modified MIT license. Architecturally it shares the dense Ministral-3 text backbone with mistralai/Devstral-2-123B-Instruct-2512. This commit adds the documentation for that model: - docs/model-coverage/vlm/mistralai/mistral-medium-3-5.md: model coverage page covering architecture (dense, 88-layer Ministral-3 text backbone + Pixtral vision tower), strengths/trade-offs, use cases, recipe, install/run snippets. Modeled on mistral-small-4.md. - docs/guides/vlm/mistral-medium-3-5.md: end-to-end fine-tuning guide on MedPix-VQA with the 8-node TP=8 PP=8 recipe, including a walkthrough of the FP8 dequantize-on-load path. Modeled on the Qwen3.5-VL guide. - docs/model-coverage/vlm/index.md: add Mistral Medium 3.5 row to supported models table and toctree. - docs/model-coverage/latest-models.md: prepend release row. - docs/index.md: add Mistral Medium 3.5 VL to the guides toctree. - README.md: add news bullet. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> Signed-off-by: HuiyingLi <willwin.lee@gmail.com>
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Summary
Mistral3FP8VLMForConditionalGeneration), TP plan, PP forward, and 8-node MedPix recipe. This PR is documentation-only.🤖 Generated with Claude Code