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Qwen3 Coder 480B A35B Instruct

AlibabaQwen開源權重Apache 2.0 · 商用許可

描述

Qwen3-Coder-480B-A35B-Instruct is Qwen's most agentic code model to date, featuring 480 billion total parameters with 35 billion activated parameters using MoE architecture. It achieves significant performance among open models on Agentic Coding, Agentic Browser-Use, and foundational coding tasks, with results comparable to Claude Sonnet. Features native 256K token context length (extendable to 1M tokens with Yarn), optimized for repository-scale understanding, and specialized function call format for agentic coding platforms like Qwen Code and CLINE.

發布日期
2025-07-22
參數規模
480.0B
上下文長度
262K
支援模態
text

能力雷達圖

34
general
53
coding
52
reasoning
41
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116
36.0
LS
程式碼能力榜238
49.0
AA
通用能力榜292
45.0
AA
科學能力332
42.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Agents

BFCL-v368.7%自報
MM-Mind2Web55.8%自報
Terminal-Bench 2.0Stanford × Laude Institute (2026)37.5%自報

Code

SWE-Bench Verified69.6%自報
Aider-Polyglot61.8%自報
SWE-bench Multilingual54.7%自報
Multi-SWE-Bench25.8%自報

Communication

TAU-bench Retail77.5%自報
TAU-bench Airline60.0%自報

Language

Spider31.1%自報

AA 評測指數

(Artificial Analysis)
Math Index(Artificial Analysis)
39.3
Intelligence Index(Artificial Analysis)
18.2
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
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.6
Aime(MAA (Mathematical Association of America))
0.5
Lcr(Artificial Analysis)
0.5
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.4
Ifbench(Google Research (2023))
0.4
Aime 25(MAA (Mathematical Association of America))
0.4
Scicode(UIUC + Argonne National Lab (2024))
0.4
Terminalbench Hard(Stanford × Laude Institute (2026))
0.2
Hle(Center for AI Safety + Scale AI (2025))
0.0

LLM Stats 分類評分

(LLM Stats (zeroeval))
Structured Output
70
Finance
70
Communication
70
Multimodal
60
Reasoning
60
Frontend Development
60
General
60
Tool Calling
60
Agents
50
Code
50

定價

輸入價格$1.5 / 1M tokens
輸出價格$7.5 / 1M tokens
混合價格(3:1)$3 / 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

4 個供應商

最便宜: LLM Gateway最貴: Alibaba
供應商輸入輸出
1LLM Gateway最便宜
$0.3
$1.3
2302.AI
$0.86
$3.43
3Alibaba (China)
$0.861
$3.441
4Alibaba主要
$1.5
$7.5

比較該模型在不同 API 供應商之間的定價。

外部連結

LLM StatsArtificial Analysis