# MiniMax Sparse Attention

MiniMax open-sourced MiniMax-M3.1-Flash, and vLLM supports it on day one on NVIDIA Blackwell, NVIDIA Rubin and AMD MI350-series GPUs. The model is quantization-aware trained for an NVFP4 KV cache and stores its routed MoE weights in NVFP4, shrinking the checkpoint from 451.5 GB to 250.1 GB and the KV cache from 61,440 to 34,560 bytes per token. On four NVIDIA B300 GPUs with DEP4 deployment and 256K-token sequences, M3.1 fits 76 concurrent sequences where M3 with an FP8 KV cache fits 28.

MiniMax open-sourced MiniMax-M3.1-Flash, and vLLM supports it on day one on NVIDIA Blackwell, NVIDIA Rubin and AMD MI350-series GPUs. The model is quantization-aware trained for an NVFP4 KV cache and stores its routed MoE weights in NVFP4, shrinking the checkpoint from 451.5 GB to 250.1 GB and the KV cache from 61,440 to 34,560 bytes per token. On four NVIDIA B300 GPUs with DEP4 deployment and 256K-token sequences, M3.1 fits 76 concurrent sequences where M3 with an FP8 KV cache fits 28.