MiniMax: MiniMax M2
By Minimax
Released: 2025-10-23
Minimax Minimax M2, developed by MiniMax, features 197k-token context window. MiniMax-M2 is a compact, high-efficiency large language model optimised for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning, tool use, and multi-step task execution while maintaining low latency and deployment efficiency. The model excels in code generation, multi-file editing, compile-run-fix loops, and test-validated repair, showing strong results on SWE-Bench Verified, Multi-SWE-Bench, and Terminal-Bench. It also performs competitively in agentic evaluations such as BrowseComp and GAIA, effectively handling long-horizon planning, retrieval, and recovery from execution errors. Benchmarked by [Artificial Analysis](https://artificialanalysis.ai/models/minimax-m2), MiniMax-M2 ranks among the top open-source models for composite intelligence, spanning mathematics, science, and instruction-following. Its small activation footprint enables fast inference, high concurrency, and improved unit economics, making it well-suited for large-scale agents, developer assistants, and reasoning-driven applications that require responsiveness and cost efficiency. To avoid degrading this model's performance, MiniMax highly recommends preserving reasoning between turns. Learn more about using reasoning_details to pass back reasoning in our [docs](https://openrouter.ai/docs/use-cases/reasoning-tokens#preserving-reasoning-blocks). Available at $0.2/1M tokens.
Visit MiniMax: MiniMax M2AI-Powered
Leverages advanced AI technology to deliver cutting-edge capabilities and results.
Fast & Efficient
Optimized performance ensures quick results without compromising on quality.
Purpose-Built
Specifically designed for llms tasks and workflows.
Minimax Model Timeline
33k tokens context
197k tokens context
197k tokens context
1,000k tokens context
1,000k tokens context
Specifications
AI Evaluation
Optimized for programming tasks, this model excels at code generation, debugging, and software engineering workflows with solid benchmark performance.
Pros
- Competitive pricing ($0.2/1M)
- 197k token context window
- Strong code generation and debugging
- Advanced logical reasoning
Cons
- May lack creative flair
- Speed/quality trade-off
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