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Qwen3 VL 8B (Reasoning)

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
2025-10-14
參數規模
9.0B
上下文長度
131K
支援模態
image, text

能力雷達圖

28
general
35
coding
35
reasoning
41
science
60
agents
100
multimodal

排行榜排名

領域#排名分數來源
程式碼能力榜453
27.0
AA
通用能力榜422
33.0
AA
多模態榜130
34.0
LS
科學能力473
30.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Chat

MM-MT-Bench8.00 / 100自報
IFEvalGoogle Research (2023)83.2%自報
Multi-IF75.1%自報

Creativity

Creative Writing v382.4%自報

Factuality

SimpleQA49.6%自報

General

MMLU85.2%自報
MLVU-M75.1%自報
Include69.5%自報
BFCL-v363.0%自報
Arena-Hard v251.1%自報

Language

MMLU-Redux88.8%自報
MMLU-Pro77.3%自報
MMLU-ProX70.7%自報

Math

MathVista-Mini81.4%自報
AIME 202580.3%自報
LiveBench 2024112569.8%自報
MathVision62.7%自報
HMMT2560.6%自報
PolyMATH47.5%自報

Multimodal

VideoMMMU72.8%自報
Video-MME71.8%自報
OSWorld33.9%自報

Reasoning

CharXiv-D85.9%自報
GPQANYU + Cohere + Anthropic (2023)69.9%自報
LiveCodeBench v658.6%自報
CharXiv-R53.0%自報
SuperGPQA51.2%自報

Video

CharadesSTA59.9%自報

Vision

DocVQAtest95.3%自報
ScreenSpot93.6%自報
MMBench-V1.187.5%自報
InfoVQAtest86.0%自報
AI2D84.9%自報
OCRBench81.9%自報
MuirBench76.8%自報
CC-OCR76.3%自報
MMStar75.3%自報
MMMU (val)74.1%自報
RealWorldQA73.5%自報
MVBench69.0%自報
BLINK68.7%自報
Hallusion Bench65.4%自報
OCRBench-V2 (en)63.9%自報
MMMU-Pro60.4%自報
OCRBench-V2 (zh)59.2%自報
LVBench55.8%自報
ERQA46.8%自報
ScreenSpot Pro46.6%自報
ODinW39.8%自報

Writing

WritingBench85.5%自報

AA 評測指數

(Artificial Analysis)
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
74.9
Gpqa(NYU + Cohere + Anthropic (2023))
57.9
Ifbench(Google Research (2023))
39.9
Livecodebench(UC Berkeley + MIT + Cornell (2024))
35.3
Lcr(Artificial Analysis)
33.3
Math Index(Artificial Analysis)
30.7
Aime 25(MAA (Mathematical Association of America))
30.7
Tau2(Sierra + U Toronto + Vector Institute (2025))
22.5
Intelligence Index(Artificial Analysis)
8.2
Hle(Center for AI Safety + Scale AI (2025))
3.8
Terminalbench Hard(Stanford × Laude Institute (2026))
3.8

LLM Stats 分類評分

(LLM Stats (zeroeval))
Chat
3
Communication
3
Multimodal
100
Instruction Following
80
Language
80
Structured Output
80
General
80
Text-to-image
80
Image To Text
70
Legal
70
Math
70
Reasoning
70
Finance
70
Grounding
70
Healthcare
70
3d
70
Biology
70
Creativity
70
Vision
70
Writing
70
Long Context
60
Physics
60
Spatial Reasoning
60
Chemistry
60
Tool Calling
60
Video
60
Factuality
50
Agents
50
Economics
50

定價

輸入價格$0.18 / 1M tokens
輸出價格$2.1 / 1M tokens
混合價格(3:1)$0.66 / 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: Alibaba最貴: Kilo Gateway
供應商輸入輸出
1Alibaba主要
$0.18
$2.1
2OpenRouter
$0.18
$2.1
3Kilo Gateway
$0.18
$2.1

比較該模型在不同 API 供應商之間的定價。

外部連結