ChainCatcher report: On October 23, MiniMax announced the open-sourcing of the MiniMax M3.1 Flash model weights, with a total of 428 billion parameters and 23 billion activated parameters. Compared to the previous-generation M3 model, M3.1 Flash delivers comprehensive improvements in model capabilities. According to official data, within 72 hours of its release, the model processed over 100 trillion tokens from real users. Technically, M3.1 Flash enhances inference efficiency through optimizations such as full-model sparse attention, quantization-aware training (QAT), and power-aware scheduling. In terms of ecosystem, MiniMax has collaborated with chip manufacturers including Huawei Ascend, Pingtouge, Kunlunxin, Moore Threads, Bitmain, Hygon, Musen, TianShu, NVIDIA, and AMD, as well as cloud platforms such as Together AI, Fireworks, Nebius, Baseten, Modal, and DigitalOcean to enable integration on the first day of open-sourcing. The community has also provided simultaneous support for deploying the model across diverse chips and development environments through vLLM, SGLang, Baidu’s FlagOS, Hugging Face, and ModelScope.
The MiniMax M3.1 Flash Model processes over 100 trillion tokens in 72 hours.
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Summary
The MiniMax M3.1 Flash model, a major token launch event, processes over 100 trillion tokens in 72 hours. The model features 428 billion total parameters and 23 billion active parameters. On-chain data shows it utilizes full-model sparse attention, QAT, and power-aware scheduling. Partners include Huawei Ascend, NVIDIA, and cloud platforms such as Together AI.
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