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Qwen3 235B A22B 2507 (Reasoning)

AlibabaQwen開源權重Apache 2.0 · 商用許可

描述

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.

發布日期
2025-07-25
參數規模
235.0B
上下文長度
262K
支援模態
text

能力雷達圖

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

排行榜排名

領域#排名分數來源
智慧體能力模型榜45
53.0
LS
程式碼能力榜219
50.0
AA
通用能力榜222
52.0
AA
科學能力165
59.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Agents

BFCL-v371.9%自報

Biology

GPQANYU + Cohere + Anthropic (2023)81.1%自報

Chemistry

SuperGPQA64.9%自報

Code

CFEval2134.00 / 10000自報

Communication

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

Creativity

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

Finance

MMLU-Pro84.4%自報
MMLU-ProX81.0%自報

General

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

Math

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

Reasoning

OJBench32.5%自報

AA 評測指數

(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 分類評分

(LLM Stats (zeroeval))
Instruction Following
80
Language
80
Legal
80
Structured Output
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

定價

輸入價格$0.7 / 1M tokens
輸出價格$8.4 / 1M tokens
混合價格(3:1)$2.625 / 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

5 個供應商

最便宜: OpenRouter最貴: Alibaba
供應商輸入輸出
1OpenRouter最便宜
$0.23
$2.3
2Kilo Gateway
$0.23
$2.3
3Jiekou.AI
$0.3
$3
4NovitaAI
$0.3
$3
5Alibaba主要
$0.7
$8.4

比較該模型在不同 API 供應商之間的定價。

外部連結