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

Fonctionnalités

API sans serveur

Documentation

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.

Sans serveur disponible

Exécutez des requêtes immédiatement, ne payez que pour l’utilisation

Entrée$0.3 / M Tokens

Lecture du cache$0.03 / M Tokens

Sortie$1.2 / M Tokens

Utilisez les exemples de code suivants pour intégrer notre 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)

Infos

Fournisseur

MiniMax

Quantification

fp8

Fonctionnalités prises en charge

Longueur du contexte

204800

Sortie maximale

131072

Serverless

Pris en charge

Function Calling

Pris en charge

Structured Output

Pris en charge

Reasoning

Pris en charge

API Anthropic

Pris en charge

Capacités d’entrée

text

Capacités de sortie

text