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MiniMax-M2.1

MiniMaxMiniMaxओपन वेटMIT · व्यावसायिक उपयोग

विवरण

MiniMax M2.1 is an enhanced large language model focused on multi-language programming and real-world complex tasks. It features exceptional capabilities across Rust, Java, Golang, C++, Kotlin, Objective-C, TypeScript, JavaScript and more, with industry-leading multilingual performance that outperforms Claude Sonnet 4.5 and approaches Claude Opus 4.5. M2.1 significantly strengthens native Android and iOS development, delivers enhanced design comprehension and aesthetic expression for web/app scenarios, and provides more concise responses with improved speed and reduced token consumption. It excels across various coding agent frameworks including Claude Code, Droid (Factory AI), Cline, Kilo Code, Roo Code, and BlackBox.

रिलीज़ तिथि
2025-12-23
पैरामीटर
230.0B
संदर्भ लंबाई
205K
मोडैलिटीज़
text

क्षमता रडार

41
general
81
coding
83
reasoning
65
science
70
agents
0
multimodal

रैंकिंग

बेंचमार्क स्कोर (LLM Stats)

(LLM Stats (zeroeval))

Agents

Toolathlon43.5%स्वयं

Code

VIBE Web91.5%स्वयं
VIBE Android89.7%स्वयं
VIBE88.6%स्वयं
VIBE iOS88.0%स्वयं
VIBE Simulation87.1%स्वयं
VIBE Backend86.7%स्वयं
SWT-Bench69.3%स्वयं
OctoCodingBench26.1%स्वयं
SWE-Review8.9%स्वयं
SWE-Perf3.1%स्वयं

Communication

Tau2 Telecom87.0%स्वयं

Instruction Following

IFBench70.0%स्वयं

Language

MMLU-Pro88.0%स्वयं

Math

AIME 202581.0%स्वयं

Reasoning

GPQANYU + Cohere + Anthropic (2023)81.0%स्वयं
LiveCodeBench78.0%स्वयं
SWE-bench Multilingual72.5%स्वयं
SWE-Bench Verified67.0%स्वयं
AA-LCR62.0%स्वयं
BrowseCompOpenAI (2025)62.0%स्वयं
Multi-SWE-Bench49.4%स्वयं
Terminal-Bench47.9%स्वयं
SciCode39.0%स्वयं
Humanity's Last Exam22.0%स्वयं

AA मूल्यांकन सूचकांक

(Artificial Analysis)
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
87.5
Tau2(Sierra + U Toronto + Vector Institute (2025))
85.4
Gpqa(NYU + Cohere + Anthropic (2023))
83.0
Math Index(Artificial Analysis)
82.7
Aime 25(MAA (Mathematical Association of America))
82.7
Livecodebench(UC Berkeley + MIT + Cornell (2024))
81.0
Ifbench(Google Research (2023))
69.9
Lcr(Artificial Analysis)
67.7
Terminalbench Hard(Stanford × Laude Institute (2026))
28.8
Hle(Center for AI Safety + Scale AI (2025))
23.2
Intelligence Index(Artificial Analysis)
20.9

LLM Stats श्रेणी स्कोर

(LLM Stats (zeroeval))
Language
90
Legal
90
Finance
90
Healthcare
90
Communication
90
Instruction Following
70
Frontend Development
70
Tool Calling
70
Long Context
60
Math
60
Physics
60
Reasoning
60
Search
60
General
60
Biology
60
Chemistry
60
Code
60
Agents
50
Vision
20

मूल्य निर्धारण

इनपुट मूल्य$0.3 / 1M टोकन
आउटपुट मूल्य$1.2 / 1M टोकन
मिश्रित मूल्य (3:1)$0.525 / 1M टोकन
कैश पठन मूल्य$0.03 / 1M टोकन
कैश लेखन मूल्य$0.375 / 1M टोकन

गति

टोकन/सेकंड0.0
पहले टोकन में देरी0.00s
पहले उत्तर में देरी0.00s

प्रदाता मूल्य रैंकिंग

प्रदाता मूल्य रैंकिंग

15 प्रदाता

सबसे सस्ता: MiniMaxसबसे महंगा: Moark
प्रदाताइनपुटआउटपुट
1MiniMaxसबसे सस्ता
$0
$0
2LLM Gateway
$0.27
$1.1
3302.AI
$0.3
$1.2
4OpenRouter
$0.3
$1.2
5Jiekou.AI
$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
$0.33
$1.32
15Moark
$2.1
$8.4

इस मॉडल के लिए विभिन्न API प्रदाताओं के मूल्य निर्धारण की तुलना करें।

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