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MiniMax M2.5 released: 80.2% in SWE-bench Verified
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Overview
MiniMax M2.5 is a state-of-the-art AI model designed for real-world productivity, achieving scores of 80.2% in SWE-Bench Verified, 51.3% in Multi-SWE-Bench, and 76.3% in BrowseComp. It has been extensively trained using reinforcement learning across hundreds of thousands of complex environments, excelling in coding, agentic tool use, search, and office tasks.
Summary from minimax.io.
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Hacker News · minimax.io
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Based on 5 sampled comments from this thread. Analyzed 2026-02-12.
- Praise: MiniMax M2.1 is favored for its speed, cost-effectiveness, and excellent tool calling capabilities, making it a top choice in AI workflows.
- Praise: The model is currently free on OpenCode, which enhances accessibility for developers looking to experiment with advanced AI tools.
- Praise: The balance of speed, quality, and cost in MiniMax models makes them appealing for various applications, including coding and analysis.
- Concern: Some users express skepticism about the benchmarks, suggesting they may be too good to be true and questioning the novelty of the training methods.
- Concern: Concerns about the limitations of available LLMs in corporate environments highlight the challenges of accessing diverse AI models.