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MiniMax-M2

MiniMaxMiniMaxOpen WeightMIT · Commercial OK

Description

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.

Release Date
2025-10-26
Parameters
230.0B
Context Length
205K
Modalities
text

Capability Radar

37
general
83
coding
78
reasoning
58
science
80
agents
0
multimodal

Rankings

Domain#RankScoreSource
Code Ranking196
67.0
AA
General Ranking118
64.0
AA
Science256
50.0
AA

Benchmark Scores (LLM Stats)

(LLM Stats (zeroeval))

Communication

Tau2 Telecom87.0%SR

General

Tau-bench77.2%SR
IF72.0%SR
AA-Index61.0%SR

Language

MMLU-Pro82.0%SR

Math

AIME 202578.0%SR

Reasoning

LiveCodeBench83.0%SR
GPQANYU + Cohere + Anthropic (2023)78.0%SR
SWE-Bench Verified69.4%SR
SWE-bench Multilingual56.5%SR
BrowseComp-zh48.5%SR
Terminal-Bench46.3%SR
BrowseCompOpenAI (2025)44.0%SR
Multi-SWE-Bench36.2%SR
SciCode36.0%SR
Humanity's Last Exam12.5%SR

AA Evaluation Indices

(Artificial Analysis)
Tau2(Sierra + U Toronto + Vector Institute (2025))
86.8
Livecodebench(UC Berkeley + MIT + Cornell (2024))
82.6
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
82.0
Aime 25(MAA (Mathematical Association of America))
78.3
Math Index(Artificial Analysis)
78.3
Gpqa(NYU + Cohere + Anthropic (2023))
77.7
Ifbench(Google Research (2023))
72.3
Lcr(Artificial Analysis)
64.3
Terminalbench Hard(Stanford × Laude Institute (2026))
25.8
Intelligence Index(Artificial Analysis)
18.6
Hle(Center for AI Safety + Scale AI (2025))
13.7

LLM Stats Category Scores

(LLM Stats (zeroeval))
Communication
90
Language
80
Legal
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

Pricing

Input Price$0.3 / 1M tokens
Output Price$1.2 / 1M tokens
Blended Price (3:1)$0.525 / 1M tokens

Speed

Tokens/sec0.0
Time to First Token0.00s
Time to Answer0.00s

Provider Price Ranking

Provider Price Ranking

16 providers

Cheapest: MiniMaxMost Expensive: Cortecs
ProviderInputOutput
1MiniMaxCheapest
$0
$0
2Novita
$0
$0
3DevPass (LLM Gateway)
$0.2
$1
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 (minimax.cn)
$0.3
$1.2
12Merge Gateway
$0.3
$1.2
13Ofox
$0.3
$1.2
14NanoGPT
$0.302
$1.207
15302.AI
$0.33
$1.32
16Cortecs
$0.349
$1.405

Compare pricing across different API providers for this model.

External Sources