MiniMax-M3.1-Flash is a multimodal model from MiniMax. Compared with M3, it delivers significant improvements across multiple benchmarks, particularly in complex agentic tasks, coding, and cybersecurity. It is built for complex, multi-step co-work automation, understanding real codebases, fixing bugs, and building features, and visual understanding and creation, including frontend and presentation creation. Open weights are planned.
MiniMax-M2.7 is a large language model built for autonomous, real-world productivity and continuous improvement. Designed to take an active role in its own development, M2.7 incorporates advanced agent capabilities through multi-agent collaboration, allowing it to plan, execute, and improve complex tasks across dynamic environments. Trained for production-level performance, M2.7 supports workflows such as live debugging, root cause analysis, financial modeling, and full document creation across Word, Excel, and PowerPoint. It delivers strong benchmark results, including 56.2% on SWE-Pro and 57.0% on Terminal Bench 2, while reaching 1495 ELO on GDPval-AA, setting a new benchmark for multi-agent systems in real-world digital workflows.