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Qwen3 235B A22B (Non-reasoning)

AlibabaQwen开源权重Apache 2.0 · 商用许可

描述

Qwen3 235B A22B is a large language model developed by Alibaba, featuring a Mixture-of-Experts (MoE) architecture with 235 billion total parameters and 22 billion activated parameters. It achieves competitive results in benchmark evaluations of coding, math, general capabilities, and more, compared to other top-tier models.

发布日期
2025-04-28
参数规模
235.0B
上下文长度
131K
支持模态
text

能力雷达图

29
general
33
coding
40
reasoning
39
science
70
agents
0
multimodal

排行榜排名

领域#排名分数来源
代码能力榜470
15.0
AA
通用能力榜374
35.0
AA
科学能力362
39.0
AA

基准测试分数 (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)47.5%自报

Chemistry

SuperGPQA44.1%自报

Code

EvalPlus0.78 / 100自报
LiveCodeBench70.7%自报
Aider61.8%自报

Creativity

Arena Hard95.6%自报

Finance

MMLU87.8%自报
MMLU-Pro68.2%自报

General

MMLU-Redux87.4%自报
MMMLU86.7%自报
MBPP0.81 / 100自报
LiveBench77.1%自报
Include73.5%自报
MultiLF71.9%自报
BFCL70.8%自报
MultiPL-E65.9%自报

Language

BBH88.9%自报

Math

GSM8k94.4%自报
AIME 202485.7%自报
MGSM83.5%自报
AIME 202581.5%自报
MATH71.8%自报

Reasoning

CRUX-O0.79 / 100自报

AA 评测指数

(Artificial Analysis)
Math Index(Artificial Analysis)
23.7
Intelligence Index(Artificial Analysis)
10.8
Math 500(OpenAI (2024), subset of Hendrycks et al. MATH (2021))
0.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.8
Gpqa(NYU + Cohere + Anthropic (2023))
0.6
Ifbench(Google Research (2023))
0.4
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.3
Aime(MAA (Mathematical Association of America))
0.3
Scicode(UIUC + Argonne National Lab (2024))
0.3
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.3
Aime 25(MAA (Mathematical Association of America))
0.2
Terminalbench Hard(Stanford × Laude Institute (2026))
0.1
Hle(Center for AI Safety + Scale AI (2025))
0.0
Lcr(Artificial Analysis)
0.0

LLM Stats 分类评分

(LLM Stats (zeroeval))
Creativity
100
Writing
100
Math
80
Reasoning
80
Language
80
General
80
Legal
70
Finance
70
Healthcare
70
Code
70
Tool Calling
70
Physics
50
Biology
50
Chemistry
50
Economics
40

定价

输入价格$0.7 / 1M tokens
输出价格$2.8 / 1M tokens
混合价格(3:1)$1.225 / 1M tokens

速度

Tokens/秒0.0
首Token延迟0.00s
首回答延迟0.00s

供应商价格排行

供应商价格排行

1 个供应商

供应商输入输出
1Alibaba主要
$0.7
$2.8

比较该模型在不同 API 供应商之间的定价。

外部链接