MiniMax Launches M2.5 AI Model with Enhanced Performance in Coding and Real-World Tasks
By
denysvitali
Baker's choice. Dense with flavour, light on filler.
Summary
MiniMax introduces its latest AI model, M2.5, which has been extensively trained with reinforcement learning in complex real-world environments. The model achieves state-of-the-art performance in coding, agentic tool use, search, office work, and other economically valuable tasks. It demonstrates significant improvements in benchmark scores including 80.2% in SWE-Bench Verified, 51.3% in Multi-SWE-Bench, and 76.3% in BrowseComp with context management. The model is optimized for efficient reasoning and task decomposition, completing the SWE-Bench Verified evaluation 37% faster than its predecessor M2.
Key quotes
· 4 pulledExtensively trained with reinforcement learning in hundreds of thousands of complex real-world environments, M2.5 is SOTA in coding, agentic tool use and search, office work, and a range of other economically valuable tasks
boasting scores of 80.2% in SWE-Bench Verified, 51.3% in Multi-SWE-Bench, and 76.3% in BrowseComp (with context management)
Trained to reason efficiently and decompose tasks optimally, M2.5 exhibits tremendous speed in performing complicated agentic tasks
completing the SWE-Bench Verified evaluation 37% faster than M2
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