Model Library/MiniMax-M2
minimax/minimax-m2

MiniMax-M2

minimax/minimax-m2
MiniMax-M2 is a compact, high-efficiency large language model optimized 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, 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, d

Recursos

API serverless

Documentação

minimax/minimax-m2 is available via Novita's serverless API, where you pay per token. There are several ways to call the API, including OpenAI-compatible endpoints with exceptional reasoning performance.

Serverless disponível

Execute consultas imediatamente, pague apenas pelo uso

Entrada$0.3 / M Tokens
Leitura de cache$0.03 / M Tokens
Saída$1.2 / M Tokens

Use os exemplos de código a seguir para integrar com nossa API:

1from openai import OpenAI
2
3client = OpenAI(
4    api_key="<Your API Key>",
5    base_url="https://api.novita.ai/openai"
6)
7
8response = client.chat.completions.create(
9    model="minimax/minimax-m2",
10    messages=[
11        {"role": "system", "content": "You are a helpful assistant."},
12        {"role": "user", "content": "Hello, how are you?"}
13    ],
14    max_tokens=131072,
15    temperature=0.7
16)
17
18print(response.choices[0].message.content)

Informações

Provedor
MiniMax
Quantização
fp8

Funcionalidades compatíveis

Comprimento do contexto
204800
Saída máxima
131072
Serverless
Compatível
Function Calling
Compatível
Structured Output
Compatível
Reasoning
Compatível
API da Anthropic
Compatível
Capacidades de entrada
text
Capacidades de saída
text