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MiniMax-M2

MiniMaxMiniMaxOpen WeightMIT · Uso Comercial

Descripción

MiniMax M2 is an open-source large language model by MiniMax, built for agents and coding tasks. It delivers state-of-the-art tool use, reasoning, and search performance while maintaining exceptional cost-efficiency and speed, priced at just 8% of Claude 3.5 Sonnet’s cost and running at nearly double its inference speed (≈100 TPS). Designed for end-to-end agentic workflows, it excels at long-chain tool calling across Shell, Browser, Python, and other MCP tools. While slightly behind top overseas models in programming, it ranks among the best domestic models and top five globally on the Artificial Analysis benchmark. M2 powers the MiniMax Agent platform, available in Lightning Mode for fast tasks and Pro Mode for complex multi-step reasoning, and its weights, API, and deployment guides are freely available on Hugging Face, vLLM, and SGLang.

Fecha de lanzamiento
2025-10-26
Parámetros
230.0B
Longitud del contexto
197K
Modalidades
text

Radar de capacidades

43
general
72
coding
78
reasoning
50
science
80
agents
0
multimodal

Rankings

Dominio#PosiciónPuntuaciónFuente
Capacidad agéntica77
45.0
LS
Ranking de codificación123
69.0
AA
Ranking general104
71.0
AA
Ciencia213
54.0
AA

Puntuaciones de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Agents

Tau-bench77.2%Aut.
Terminal-Bench46.3%Aut.
BrowseCompOpenAI (2025)44.0%Aut.

Biology

GPQANYU + Cohere + Anthropic (2023)78.0%Aut.
SciCode36.0%Aut.

Code

LiveCodeBench83.0%Aut.
SWE-Bench Verified69.4%Aut.
SWE-bench Multilingual56.5%Aut.
Multi-SWE-Bench36.2%Aut.

Communication

Tau2 Telecom87.0%Aut.

Finance

MMLU-Pro82.0%Aut.

General

IF72.0%Aut.
AA-Index61.0%Aut.

Math

AIME 202578.0%Aut.
Humanity's Last Exam12.5%Aut.

Reasoning

BrowseComp-zh48.5%Aut.

Índices de evaluación AA

(Artificial Analysis)
Math Index(Artificial Analysis)
78.3
Intelligence Index(Artificial Analysis)
28.9
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.9
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.8
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.8
Aime 25(MAA (Mathematical Association of America))
0.8
Gpqa(NYU + Cohere + Anthropic (2023))
0.8
Ifbench(Google Research (2023))
0.7
Lcr(Artificial Analysis)
0.7
Scicode(UIUC + Argonne National Lab (2024))
0.4
Terminalbench Hard(Stanford × Laude Institute (2026))
0.3
Hle(Center for AI Safety + Scale AI (2025))
0.1

Puntuaciones por categoría LLM Stats

(LLM Stats (zeroeval))
Communication
90
Legal
80
Language
80
Finance
80
Healthcare
80
Tool Calling
80
Frontend Development
70
Physics
60
Reasoning
60
General
60
Agents
60
Biology
60
Chemistry
60
Math
50
Search
50
Code
50
Vision
10

Precios

Precio de entrada$0.3 / 1M tokens
Precio de salida$1.2 / 1M tokens
Precio mixto (3:1)$0.525 / 1M tokens

Velocidad

Tokens/seg0.0
Retraso del primer token0.00s
Tiempo hasta la respuesta0.00s

Ranking de Precios por Proveedor

Ranking de Precios por Proveedor

14 proveedores

Más barato: MiniMaxMás caro: Cortecs
ProveedorEntradaSalida
1MiniMaxMás barato
$0
$0
2Novita
$0
$0
3NanoGPT
$0.17
$1.53
4LLM Gateway
$0.2
$1
5OpenRouter
$0.3
$1.2
6ZenMux
$0.3
$1.2
7NovitaAI
$0.3
$1.2
8Kilo Gateway
$0.3
$1.2
9Vercel AI Gateway
$0.3
$1.2
10MiniMax (minimax.io)
$0.3
$1.2
11MiniMax (minimaxi.com)
$0.3
$1.2
12Merge Gateway
$0.3
$1.2
13302.AI
$0.33
$1.32
14Cortecs
$0.349
$1.405

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas