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Qwen3 VL 32B Instruct

AlibabaQwen開源權重Apache 2.0 · 商用許可

描述

Qwen3-VL is a large multimodal model that unifies vision, language, and reasoning to achieve human-level perception and cognition across text, images, and video. Built on a 235B-parameter architecture, it integrates early joint training of visual and textual modalities for strong language grounding. The model supports up to a 1 million-token context window and excels at visual understanding, spatial reasoning, long video comprehension, and tool-based interaction. It can generate code from images, perform precise 2D/3D object grounding, and operate digital interfaces like a visual agent. The “Instruct” version rivals Gemini 2.5 Pro in perception benchmarks, while the “Thinking” version leads in multimodal reasoning and STEM tasks. With multilingual OCR, creative writing, and fine-grained scene interpretation, Qwen3-VL establishes a new open-source frontier for integrated vision-language intelligence.

發布日期
2025-10-21
參數規模
33.0B
上下文長度
131K
支援模態
image, text

能力雷達圖

29
general
51
coding
68
reasoning
49
science
70
agents
90
multimodal

排行榜排名

領域#排名分數來源
程式碼能力榜393
35.0
AA
通用能力榜394
35.0
AA
多模態榜79
52.0
LS
科學能力392
38.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Chat

MM-MT-Bench8.40 / 100自報
IFEvalGoogle Research (2023)84.7%自報
Multi-IF72.0%自報

Creativity

Creative Writing v385.6%自報

General

MMLU86.4%自報
MLVU-M82.1%自報
Include74.0%自報
BFCL-v370.2%自報
Arena-Hard v264.7%自報

Language

MMLU-Redux89.8%自報
MMLU-Pro78.6%自報
MMLU-ProX73.4%自報

Math

MathVista-Mini83.8%自報
LiveBench 2024112572.2%自報
AIME 202566.2%自報
MathVision63.4%自報
PolyMATH40.5%自報

Multimodal

OSWorld32.6%自報

Reasoning

CharXiv-D90.5%自報
GPQANYU + Cohere + Anthropic (2023)68.9%自報
CharXiv-R62.8%自報
SuperGPQA54.6%自報
LiveCodeBench v643.8%自報

Video

CharadesSTA61.2%自報

Vision

DocVQAtest96.9%自報
ScreenSpot95.8%自報
OCRBench89.5%自報
AI2D89.5%自報
InfoVQAtest87.0%自報
CC-OCR80.3%自報
RealWorldQA79.0%自報
MMStar77.7%自報
MMMU (val)76.0%自報
MVBench72.8%自報
MuirBench72.8%自報
OCRBench-V2 (en)67.4%自報
BLINK67.3%自報
MMMU-Pro65.3%自報
LVBench63.8%自報
Hallusion Bench63.8%自報
OCRBench-V2 (zh)59.2%自報
ScreenSpot Pro57.9%自報
ERQA48.8%自報
ODinW46.6%自報

Writing

WritingBench82.9%自報

AA 評測指數

(Artificial Analysis)
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
79.1
Aime 25(MAA (Mathematical Association of America))
68.3
Math Index(Artificial Analysis)
68.3
Gpqa(NYU + Cohere + Anthropic (2023))
67.1
Livecodebench(UC Berkeley + MIT + Cornell (2024))
51.4
Ifbench(Google Research (2023))
39.2
Tau2(Sierra + U Toronto + Vector Institute (2025))
29.2
Intelligence Index(Artificial Analysis)
8.4
Terminalbench Hard(Stanford × Laude Institute (2026))
8.3
Hle(Center for AI Safety + Scale AI (2025))
6.8

LLM Stats 分類評分

(LLM Stats (zeroeval))
Chat
3
Communication
3
Multimodal
1
General
90
Instruction Following
80
Language
80
Legal
80
Structured Output
80
Grounding
80
Creativity
80
Text-to-image
80
Writing
80
Image To Text
70
Math
70
Reasoning
70
Spatial Reasoning
70
Finance
70
Healthcare
70
3d
70
Biology
70
Tool Calling
70
Video
70
Vision
70
Long Context
60
Physics
60
Chemistry
60
Agents
50
Economics
50

定價

輸入價格$0.16 / 1M tokens
輸出價格$0.64 / 1M tokens
混合價格(3:1)$0.28 / 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

3 個供應商

最便宜: OpenRouter最貴: Alibaba
供應商輸入輸出
1OpenRouter最便宜
$0.104
$0.416
2Kilo Gateway
$0.104
$0.416
3Alibaba主要
$0.16
$0.64

比較該模型在不同 API 供應商之間的定價。

外部連結