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MiniMax M3 Debuts, Eclipsing GPT-5.5 and Gemini 3.1 Pro on Key Benchmark Performance for Just 5-10% of the Cost

The Shanghai-based startup says the model cuts compute needs to one-twentieth of prior levels and will publish weights on HuggingFace and GitHub within 10 days.

  • On Sunday, Chinese AI startup MiniMax released its M3 large language model, featuring a 1-million-token context window and native multimodality paired with frontier-tier coding performance at reduced costs.
  • Redesigned architecture using sparse attention reduces computational requirements to 1/20th of previous levels, slashing inference costs. Standard Transformer networks scale quadratically, making long inputs prohibitively expensive.
  • The model records 59.0% on SWE-Bench Pro, outperforming Gemini 3.1 Pro, while trailing Claude Opus 4.8 on code modification tasks. M3 maintains competitive execution against DeepSeek-V4 Pro Max on agentic categories.
  • MiniMax plans to release M3 under an open-weights license within 10 days, enabling enterprise users to run the model locally. API pricing starts at $0.3 per million input tokens, undercutting proprietary U.S. competitors.
  • Developers confirmed day-one compatibility with tools like Cline, the agentic AI coding harness. In a 12-hour autonomous test, M3 produced 18 commits and 23 experimental figures, demonstrating capability for complex software engineering projects.
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MiniMax, an AI development company based in Shanghai, China, has announced its AI model, "MiniMax M3." MiniMax M3 has achieved benchmark scores that compete with GPT-5.5 and Claude Opus 4.7, and the company has stated that it will be distributed as an open model within 10 days of its announcement.

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OfficeChai broke the news on Monday, June 1, 2026.
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