MiniMaxAI/MiniMax-M2.1

What is MiniMax-M2.1?

MiniMax-M2.1 is an open-source, high-performance model released to the community to democratize top-tier "agentic" capabilities. It is built to move beyond simple text generation, serving as a robust engine for automating software development and executing complex office workflows.

Key Features

• Optimized for Agents: Specifically enhanced for robustness in coding, tool usage, instruction following, and complex planning.
• Full-Stack Capabilities: Demonstrates high proficiency in architecting functional applications across Web, Android, iOS, and Backend environments.
• Multilingual Excellence: Outperforms major models like Claude Sonnet 4.5 in multilingual software engineering benchmarks.
• Large Context Management: Includes optimized strategies for handling long-horizon tasks and extensive token usage.
• Open Access: Weights are available for local deployment via Hugging Face and supported by frameworks like SGLang, vLLM, and Transformers.

Use Cases

• Automated Software Development: Developing and maintaining software across multiple programming languages.
• Autonomous Application Building: Creating complete applications "from zero to one" using the VIBE (Visual & Interactive Benchmark for Execution) paradigm.
• Complex Office Workflows: Executing multi-step, logic-heavy business processes.
• Advanced Tool Integration: Utilizing external APIs and tools to solve long-horizon engineering problems.

FAQ (Quick Reference)

• Is there an API available? Yes, the API is live on the MiniMax Open Platform.
• Can I run it locally? Yes, model weights can be downloaded from Hugging Face.
• What are the recommended inference parameters? It is recommended to use temperature=1.0, top_p=0.95, and top_k=40.
• How does it perform against other models? In benchmarks like SWE-bench Multilingual and Multi-SWE-bench, it consistently exceeds the performance of Claude Sonnet 4.5.