ModelScope summarizes M3.1 Flash specs and scores: 62.8 Automation-Bench, 73.7% DeepSWE
ModelScope lists M3.1 Flash's 428B MoE with 23B active, 1M context and native image/video input, plus official scores like 62.8 Automation-Bench, 73.7% DeepSWE, 61.7 OSWorld 2.0 and 82.2 CyberGym, with SGLang/vLLM self-hosting guidance.
1M tokens, native image and video input, and 23B active parameters per token. MiniMax-M3.1-Flash has landed as a 428B MoE for coding, computer use, and tool-driven agents. 🤖 https://modelscope.ai/models/MiniMax/MiniMax-M3.1-Flash 📄 https://modelscope.ai/papers/2606.13392 🏆 Top result for agent execution: Scores 62.8 on Automation-Bench v1.0.6, the highest result in the model card’s reported comparison. 💻 Strong at coding and computer use: Reaches 73.7% on DeepSWE v1.1, 61.7 on OSWorld 2.0, and 29.6 on Agents’ Last Exam. 🔐 Built for cybersecurity work: Scores 82.2 on CyberGym for vulnerability discovery and validation. ⚡ Efficiency is built in: Sparse attention throughout, QAT NVFP4, and the included DSpark draft head support efficient inference and speculative decoding. 🛠️ Ready to self-host: Model weights are available with SGLang and vLLM deployment guidance.