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Qwen3 235B A22B (Non-reasoning)

AlibabaQwen開源權重Apache 2.0 · 商用許可

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.

發布日期
2025-04-28
參數規模
235.0B
上下文長度
131K
支援模態
text

能力雷達圖

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

排行榜排名

領域#排名分數來源
程式碼能力榜470
15.0
AA
通用能力榜374
35.0
AA
科學能力362
39.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)47.5%自報

Chemistry

SuperGPQA44.1%自報

Code

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

Creativity

Arena Hard95.6%自報

Finance

MMLU87.8%自報
MMLU-Pro68.2%自報

General

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

Language

BBH88.9%自報

Math

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

Reasoning

CRUX-O0.79 / 100自報

AA 評測指數

(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 分類評分

(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

定價

輸入價格$0.7 / 1M tokens
輸出價格$2.8 / 1M tokens
混合價格(3:1)$1.225 / 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

1 個供應商

供應商輸入輸出
1Alibaba主要
$0.7
$2.8

比較該模型在不同 API 供應商之間的定價。

外部連結