Skip to content

MiniMax-M3 spec decoding Blackwell - #694

Open
faradawn wants to merge 1 commit into
vllm-project:mainfrom
faradawn:minimax-m3-spec-decoding-blackwell
Open

MiniMax-M3 spec decoding Blackwell#694
faradawn wants to merge 1 commit into
vllm-project:mainfrom
faradawn:minimax-m3-spec-decoding-blackwell

Conversation

@faradawn

Copy link
Copy Markdown
Collaborator

Use Eagle3-GQA draft head and enable FLASHINFER + TRT-LLM attention for spec_decoding on Blackwell (B200/B300/GB200/GB300). Non-Blackwell NVIDIA stays on the standard Eagle3 head; AMD stays on TRITON_ATTN. Based on SemiAnalysisAI/InferenceX#2328 and SemiAnalysisAI/InferenceX#2337.

Signed-off-by: Faradawn Yang <73060648+faradawn@users.noreply.github.com>
@vercel

vercel Bot commented Jul 28, 2026

Copy link
Copy Markdown
Contributor

The latest updates on your projects. Learn more about Vercel for GitHub.

Project Deployment Actions Updated (UTC)
vllm-recipes Ready Ready Preview, Comment Jul 28, 2026 1:54pm

Request Review

@gemini-code-assist gemini-code-assist Bot left a comment

Copy link
Copy Markdown
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Code Review

This pull request introduces hardware overrides for the 'blackwell' architecture in the MiniMax-M3 model configuration, specifying speculative decoding and attention settings. The review feedback correctly identifies that the CLI arguments --attention_config.backend and --attention_config.use_trtllm_attention are non-standard in vLLM and may cause server startup failures, recommending standard alternatives.

Comment thread models/MiniMaxAI/MiniMax-M3.yaml
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

None yet

1 participant