MiniMax M2.1
MiniMax-M2.1 is a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development. With only 10 billion activated parameters, it delivers a major jump in real-world capability while maintaining exceptional latency, scalability, and cost efficiency. Compared to its predecessor, M2.1 delivers cleaner, more concise outputs and faster perceived response times. It shows leading multilingual coding performance across major systems and application languages, achieving 49.4% on Multi-SWE-Bench and 72.5% on SWE-Bench Multilingual, and serves as a versatile agent “brain” for IDEs, coding tools, and general-purpose assistance. 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.
minimax/minimax-m2.1
- Context
- 205k tokens
- Completion cap
- 131,072
- Tools
- Yes
- JSON
- Yes
- Released
- 2025-12-23
Call it from Geek Hub
Same OpenAI SDK. Change the base URL and the model id.
curl https://api.geekhub.mx/v1/chat/completions \
-H "Authorization: Bearer $GEEKHUB_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "minimax/minimax-m2.1",
"messages": [{"role": "user", "content": "Hola"}]
}'Get an API keyFrequently asked questions
- What is MiniMax M2.1?
- MiniMax-M2.1 is a lightweight, state-of-the-art large language model optimized for coding, agentic workflows, and modern application development. With only 10 billion activated parameters, it delivers a major jump in real-world capability while maintaining exceptional latency, scalability, and cost efficiency. Compared to its predecessor, M2.1 delivers cleaner, more concise outputs and faster perceived response times. It shows leading multilingual coding performance across major systems and application languages, achieving 49.4% on Multi-SWE-Bench and 72.5% on SWE-Bench Multilingual, and serves as a versatile agent “brain” for IDEs, coding tools, and general-purpose assistance. 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. MiniMax M2.1 runs on the Geek Hub API (OpenAI-compatible). Model id: minimax/minimax-m2.1.
- Is MiniMax M2.1 free?
- No. Input is $0.327 per 1M tokens and output is $1.3081 per 1M tokens on Geek Hub (markup included).
- What is the context length of MiniMax M2.1?
- MiniMax M2.1 has a 205k tokens context window. It supports up to 131,072 completion tokens.
- Does MiniMax M2.1 support tool calling and structured outputs?
- MiniMax M2.1 accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.
- When was MiniMax M2.1 released?
- MiniMax M2.1 was released on 2025-12-23.
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