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

Features

Serverless API

Docs

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.

Available Serverless

Run queries immediately, pay only for usage

Input$0.3 / M Tokens
Cache Read$0.03 / M Tokens
Output$1.2 / M Tokens

Use the following code examples to integrate with our 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)

Info

Provider
MiniMax
Quantization
fp8

Supported Functionality

Context Length
204800
Max Output
131072
Serverless
Supported
Function Calling
Supported
Structured Output
Supported
Reasoning
Supported
Anthropic API
Supported
Input Capabilities
text
Output Capabilities
text