Hugging Face Overview
MiniMax-M2.1 Overview
MiniMax-M2.1 is a 229 billion parameter large language model developed by MiniMaxAI, designed to democratize access to advanced agentic capabilities. This model is specifically optimized for robustness in coding, tool use, instruction following, and long-horizon planning, aiming to empower developers to build autonomous applications. It features a 32,768 token context length, making it suitable for complex tasks requiring extensive context.
Key Capabilities
- Advanced Agentic Performance: Optimized for complex agentic workflows, including multi-step planning and execution.
- Robust Coding: Demonstrates significant improvements in software engineering tasks, outperforming MiniMax-M2 and closely approaching Claude Opus 4.5 on benchmarks like SWE-bench Verified and Multi-SWE-bench.
- Multilingual Software Development: Excels in multilingual coding scenarios, surpassing Claude Sonnet 4.5.
- Full-Stack Application Development: Achieves an average score of 88.6 on the novel VIBE benchmark, showcasing strong capabilities in developing complete, functional applications across Web, Simulation, Android, iOS, and Backend.
- Tool Use & Instruction Following: Shows steady improvements in long-horizon tool use and comprehensive intelligence metrics, matching or exceeding Claude Sonnet 4.5 in specialized domains.
Good for
- Automating multilingual software development.
- Executing complex, multi-step office workflows.
- Building next-generation autonomous applications requiring robust coding and planning.
- Developers seeking a transparent and controllable model for agentic tasks.
- Scenarios requiring strong performance in test case generation, code optimization, and code review.