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.

On-demand Deployments

Docs

On-demand deployments allow you to use minimax/minimax-m2 on dedicated GPUs with high-performance serving stack with high reliability and no rate limits.

Available Serverless

Run queries immediately, pay only for usage

$0.3/$1.2
Per 1M Tokens (input/output)

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
bf16

Supported Functionality

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