MiniMax M3.1 Flash adds SGLang and Miles integration
MiniMax said MiniMax M3.1 Flash can run with SGLang for inference and reinforcement learning through Miles. The company claimed it exceeded 1,000 tokens per second for batch-size-1 decoding with SGLang and was production-ready from day one. The integration was described as a joint effort involving MiniMax, NVIDIA, AMD, and RadixArk, but the report included no independent throughput measurement.
SGLang support covers both inference and reinforcement learning through Miles, making the integration directly relevant to practitioners deploying MiniMax M3.1 Flash in those workflows.
From inference to RL, ready from day one. 🐰 Thanks to the teams behind SGLang, and Miles @sgl_project alongside @NVIDIAAI and @AMD, for supporting MiniMax M3.1 Flash. Great building together!
SGLang: Space Bunny is here! 🐰 MiniMax M3.1 Flash hits >1K tok/s, bs1 decode with SGLang, production-ready from Day 0. This integration is a joint effort by @MiniMax_AI, @NVIDIAAI, @AMD, and @radixark, and you can also run RL with Miles! -Broad hardware support: NVIDIA Blackwell and
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