Passer au contenu principal

Qwen3 VL 8B Instruct

AlibabaQwenOpen WeightApache 2.0 · Usage Commercial

Description

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.

Date de sortie
2025-10-14
Paramètres
9.0B
Longueur du contexte
262K
Modalités
image, text, video

Radar de capacités

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

Classements

Domaine#RangScoreSource
Classement codage520
19.0
AA
Classement général471
30.0
AA
Classement multimodal129
35.0
LS
Science566
21.0
AA

Scores de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Chat

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

General

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

Language

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

Math

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

Multimodal

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

Reasoning

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

Video

CharadesSTA56.0%Aut.

Vision

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

Writing

WritingBench83.1%Aut.

Indices d'évaluation AA

(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

Scores par catégorie LLM Stats

(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

Tarification

Prix d'entrée$0.18 / 1M tokens
Prix de sortie$0.7 / 1M tokens
Prix mixte (3:1)$0.31 / 1M tokens

Vitesse

Tokens/sec0.0
Délai du premier token0.00s
Temps de réponse0.00s

Classement des Prix par Fournisseur

Classement des Prix par Fournisseur

4 fournisseurs

Moins cher: NovitaAIPlus cher: Alibaba
FournisseurEntréeSortie
1NovitaAIMoins cher
$0.08
$0.5
2OpenRouter
$0.117
$0.455
3Kilo Gateway
$0.117
$0.455
4AlibabaPRINCIPAL
$0.18
$0.7

Comparer les prix entre différents fournisseurs API pour ce modèle.

Sources externes