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MiniMax-M2

MiniMaxMiniMax開源權重MIT · 商用許可

描述

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.

發布日期
2025-10-26
參數規模
230.0B
上下文長度
205K
支援模態
text

能力雷達圖

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

排行榜排名

領域#排名分數來源
程式碼能力榜202
67.0
AA
通用能力榜123
64.0
AA
科學能力262
50.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Communication

Tau2 Telecom87.0%自報

General

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

Language

MMLU-Pro82.0%自報

Math

AIME 202578.0%自報

Reasoning

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

AA 評測指數

(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 分類評分

(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

定價

輸入價格$0.3 / 1M tokens
輸出價格$1.2 / 1M tokens
混合價格(3:1)$0.525 / 1M tokens

速度

Tokens/秒0.0
首Token延遲0.00s
首回答延遲0.00s

供應商價格排行

供應商價格排行

16 個供應商

最便宜: MiniMax最貴: Cortecs
供應商輸入輸出
1MiniMax最便宜
$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

比較該模型在不同 API 供應商之間的定價。

外部連結