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Qwen3 235B A22B 2507 (Reasoning)

AlibabaQwenओपन वेटApache 2.0 · व्यावसायिक उपयोग

विवरण

Qwen3-235B-A22B-Thinking-2507 is a state-of-the-art thinking-enabled Mixture-of-Experts (MoE) model with 235B total parameters (22B activated). It features 94 layers, 128 experts (8 activated), and supports 262K native context length. This version delivers significantly improved reasoning performance, achieving state-of-the-art results among open-source thinking models on logical reasoning, mathematics, science, coding, and academic benchmarks. Key enhancements include markedly better general capabilities (instruction following, tool usage, text generation), enhanced 256K long-context understanding, and increased thinking depth. The model supports only thinking mode with automatic <think> tag inclusion.

रिलीज़ तिथि
2025-07-25
पैरामीटर
235.0B
संदर्भ लंबाई
262K
मोडैलिटीज़
text

क्षमता रडार

39
general
44
coding
92
reasoning
54
science
60
agents
0
multimodal

रैंकिंग

बेंचमार्क स्कोर (LLM Stats)

(LLM Stats (zeroeval))

Agents

BFCL-v371.9%स्वयं

Biology

GPQANYU + Cohere + Anthropic (2023)81.1%स्वयं

Chemistry

SuperGPQA64.9%स्वयं

Code

CFEval2134.00 / 10000स्वयं

Communication

WritingBench88.3%स्वयं
Multi-IF80.6%स्वयं
Tau2 Retail71.9%स्वयं
TAU-bench Retail67.8%स्वयं
Tau2 Airline58.0%स्वयं
TAU-bench Airline46.0%स्वयं
Tau2 Telecom45.6%स्वयं

Creativity

Creative Writing v386.1%स्वयं
Arena-Hard v279.7%स्वयं

Finance

MMLU-Pro84.4%स्वयं
MMLU-ProX81.0%स्वयं

General

MMLU-Redux93.8%स्वयं
IFEvalGoogle Research (2023)87.8%स्वयं
Include81.0%स्वयं
LiveBench 2024112578.4%स्वयं
LiveCodeBench v674.1%स्वयं

Math

AIME 202592.3%स्वयं
HMMT2583.9%स्वयं
PolyMATH60.1%स्वयं
Humanity's Last Exam18.2%स्वयं

Reasoning

OJBench32.5%स्वयं

AA मूल्यांकन सूचकांक

(Artificial Analysis)
Math Index(Artificial Analysis)
91.0
Coding Index(Artificial Analysis)
22.1
Intelligence Index(Artificial Analysis)
19.9
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
1.0
Aime(MAA (Mathematical Association of America))
0.9
Aime 25(MAA (Mathematical Association of America))
0.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.8
Gpqa(NYU + Cohere + Anthropic (2023))
0.8
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.8
Lcr(Artificial Analysis)
0.7
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.5
Ifbench(Google Research (2023))
0.5
Scicode(UIUC + Argonne National Lab (2024))
0.4
Hle(Center for AI Safety + Scale AI (2025))
0.2
Terminalbench Hard(Stanford × Laude Institute (2026))
0.1
Terminalbench V2 1
0.1
Tau Banking
0.1

LLM Stats श्रेणी स्कोर

(LLM Stats (zeroeval))
Legal
80
Structured Output
80
Instruction Following
80
Language
80
Finance
80
Healthcare
80
Biology
80
Creativity
80
Writing
80
Math
70
Physics
70
Reasoning
70
General
70
Agents
70
Chemistry
70
Communication
70
Multimodal
60
Spatial Reasoning
60
Economics
60
Tool Calling
60
Vision
40

मूल्य निर्धारण

इनपुट मूल्य$0.7 / 1M टोकन
आउटपुट मूल्य$8.4 / 1M टोकन
मिश्रित मूल्य (3:1)$2.625 / 1M टोकन

गति

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

प्रदाता मूल्य रैंकिंग

प्रदाता मूल्य रैंकिंग

6 प्रदाता

सबसे सस्ता: TensorXसबसे महंगा: Alibaba
प्रदाताइनपुटआउटपुट
1TensorXसबसे सस्ता
$0.072
$0.464
2OpenRouter
$0.23
$2.3
3Kilo Gateway
$0.23
$2.3
4Jiekou.AI
$0.3
$3
5NovitaAI
$0.3
$3
6Alibabaप्राथमिक
$0.7
$8.4

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

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