MiniMax M2.5 is a frontier language model trained with reinforcement learning across hundreds of thousands of complex real-world environments, achieving state-of-the-art scores of 80.2% on SWE-Bench Verified, 51.3% on Multi-SWE-Bench, and 76.3% on BrowseComp. Building on the coding expertise of M2.1, it extends into general office productivity — generating and operating Word, Excel, and PowerPoint files, context-switching between diverse software environments, and collaborating across agent and human teams. It completes evaluations 37% faster than M2.1 while being cost-efficient enough to run continuously for $1 per hour.
MiniMaxMiniMax M2.5 is a frontier language model trained with reinforcement learning across hundreds of thousands of complex real-world environments, achieving state-of-the-art scores of 80.2% on SWE-Bench Verified, 51.3% on Multi-SWE-Bench, and 76.3% on BrowseComp. Building on the coding expertise of M2.1, it extends into general office productivity — generating and operating Word, Excel, and PowerPoint files, context-switching between diverse software environments, and collaborating across agent and human teams. It completes evaluations 37% faster than M2.1 while being cost-efficient enough to run continuously for $1 per hour.
MiniMax