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MiniMax releases M3.1 Flash model

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On October 19, 2026, MiniMax officially launched the M3.1 Flash model, claiming improved capabilities in agents, coding, Computer Use and cybersecurity, online inference speed close to 3 times the original, and a 70% reduction in usage cost. The model reaches 82% on CyberGym and 73.7% on DeepSWE v1.1, and is already available through the MiniMax API, M Plan and MiniMax Code, with weights to be released later. An October 20 report further stated that the model scores 29.6% on Agents' Last Exam, ranking first among Chinese models, with a comprehensive cost of 30% of the previous-generation M3; it scores 76.2 on BankerToolBench, tied for first globally with Claude Opus 5; output is up to 200+ TPS, and input, output and cache read cost 1 yuan, 4 yuan and 0.1 yuan per million tokens respectively.

Generated by AI from reports · Updated 23 days ago

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Progress timeline

Oct 21
Oct 20
  1. WeChat · QbitAI
    MiniMax M3.1 Flash: Agent evaluation ALE score ranks first among domestic models, overall cost is 30% of M3

    MiniMax unveiled the official version of M3.1 Flash, whose Agents' Last Exam (ALE) score is 29.6%, ranking first among domestic models, with overall cost at 30% of the previous generation M3. It scores 73.7% on DeepSWE v1.1 and 82.2% on CyberGym, and ties for first globally with Claude Opus 5 on BankerToolBench at 76.2. Output reaches up to 200+ TPS, with input/output/cache read priced at 1 yuan, 4 yuan, and 0.1 yuan per million tokens respectively.

Oct 19
  1. XiaohongshuXiaohongshu · Max For AI· Discussion
    MiniMax released M3.1 Flash!(opens the original post in a new tab)
  2. MiniMax
    MiniMax M3.1 Flash officially released: claims to redefine agent performance and cost

    MiniMax officially launched M3.1 Flash, claiming improvements in agent, coding, Computer Use, and cybersecurity capabilities, with online inference speed nearly 3 times the original and usage cost reduced by 70%. The model reaches 82% on CyberGym and 73.7% on DeepSWE v1.1, and is already available through the MiniMax API, M Plan, and MiniMax Code, with weights to be released later.

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