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Qwen3 VL 8B 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
2025-10-14
參數規模
9.0B
上下文長度
262K
支援模態
image, text, video

能力雷達圖

25
general
33
coding
30
reasoning
30
science
70
agents
100
multimodal

排行榜排名

領域#排名分數來源
程式碼能力榜520
19.0
AA
通用能力榜471
30.0
AA
多模態榜129
35.0
LS
科學能力566
21.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Chat

MM-MT-Bench7.70 / 100自報
IFEvalGoogle Research (2023)83.7%自報
Multi-IF75.1%自報

General

MMLU80.7%自報
MLVU-M78.1%自報
Include67.0%自報
BFCL-v366.3%自報

Language

MMLU-Redux84.9%自報
MMLU-Pro71.6%自報
MMLU-ProX65.4%自報

Math

MathVista-Mini77.2%自報
LiveBench 2024112562.0%自報
MathVision53.9%自報
AIME 202545.9%自報
HMMT2532.5%自報
PolyMATH30.4%自報

Multimodal

Video-MME71.4%自報
VideoMMMU65.3%自報
OSWorld33.9%自報

Reasoning

CharXiv-D83.0%自報
CharXiv-R46.4%自報
SuperGPQA44.5%自報
LiveCodeBench v639.3%自報

Video

CharadesSTA56.0%自報

Vision

DocVQAtest96.1%自報
ScreenSpot94.4%自報
OCRBench89.6%自報
AI2D85.7%自報
MMBench-V1.185.0%自報
InfoVQAtest83.1%自報
CC-OCR79.9%自報
RealWorldQA71.5%自報
MMStar70.9%自報
MMMU (val)69.6%自報
BLINK69.1%自報
MVBench68.7%自報
OCRBench-V2 (en)65.4%自報
MuirBench64.4%自報
OCRBench-V2 (zh)61.2%自報
Hallusion Bench61.1%自報
LVBench58.0%自報
MMMU-Pro55.9%自報
ScreenSpot Pro54.6%自報
ERQA45.8%自報
ODinW44.7%自報

Writing

WritingBench83.1%自報

AA 評測指數

(Artificial Analysis)
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
68.6
Gpqa(NYU + Cohere + Anthropic (2023))
42.7
Livecodebench(UC Berkeley + MIT + Cornell (2024))
33.2
Ifbench(Google Research (2023))
32.3
Tau2(Sierra + U Toronto + Vector Institute (2025))
29.2
Aime 25(MAA (Mathematical Association of America))
27.3
Math Index(Artificial Analysis)
27.3
Lcr(Artificial Analysis)
16.7
Intelligence Index(Artificial Analysis)
7.3
Hle(Center for AI Safety + Scale AI (2025))
2.7
Terminalbench Hard(Stanford × Laude Institute (2026))
2.3

LLM Stats 分類評分

(LLM Stats (zeroeval))
Chat
3
Communication
3
Multimodal
100
Instruction Following
80
Structured Output
80
General
80
Creativity
80
Text-to-image
80
Writing
80
Image To Text
70
Language
70
Legal
70
Finance
70
Grounding
70
Healthcare
70
3d
70
Tool Calling
70
Vision
70
Long Context
60
Math
60
Reasoning
60
Spatial Reasoning
60
Video
60
Agents
50
Physics
40
Chemistry
40
Economics
40

定價

輸入價格$0.18 / 1M tokens
輸出價格$0.7 / 1M tokens
混合價格(3:1)$0.31 / 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: NovitaAI最貴: Alibaba
供應商輸入輸出
1NovitaAI最便宜
$0.08
$0.5
2OpenRouter
$0.117
$0.455
3Kilo Gateway
$0.117
$0.455
4Alibaba主要
$0.18
$0.7

比較該模型在不同 API 供應商之間的定價。

外部連結