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license: other license_name: minimax-community license_link: https://huggingface.co/MiniMaxAI/MiniMax-M3/blob/main/LICENSE base_model: MiniMaxAI/MiniMax-M3 tags: - fp8 - modelopt - quantized

MiniMax-M3-FP8 (per-tensor static, experts-quantized)

Built with MiniMax M3.

FP8 W8A8 quantization of MiniMaxAI/MiniMax-M3 produced with NVIDIA TensorRT Model Optimizer (per-tensor static scales, calibrated on a 512-sample proprietary domain-matched dataset). Scope:

• Routed MoE experts: FP8 (weights + static input scales) — 97% of parameters.
• Attention projections: BF16 — vLLM cannot load per-tensor scales on M3's fused QKV, so attention is kept high-precision by design.
• KV cache: no checkpoint-side scheme — use --kv-cache-dtype as desired.

IMPORTANT: serving requires a vLLM fix

vLLM releases to date drop MiniMax-M3's swigluoai activation constants (swiglu_alpha=1.702, swiglu_beta=1.0) in the ModelOpt FP8 MoE path, which makes this checkpoint (and any FP8 M3 checkpoint) produce incoherent output while loading without error. Fixes: vllm-project/vllm#49473 (ModelOpt path) and vllm-project/vllm#46845 (compressed-tensors path). Serve only with a build containing #49473 or with the equivalent patch applied.

vllm serve --tensor-parallel-size 8 --enable-expert-parallel --trust-remote-code --language-model-only

Quality

On an internal SWE-bench-based agentic coding evaluation (300 instances, identical harness and hardware), this checkpoint ties the official MiniMaxAI/MiniMax-M3-MXFP8 cumulative pass@1-3 (77 = 77) and resolves more instances on the first attempt (pass@1 54 vs 51).

This model inherits the MiniMax Community License of the base model, including its use restrictions and the commercial-use authorization requirement for large entities.