Passer au contenu principal

Qwen3 VL 32B 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
2025-10-21
Paramètres
33.0B
Longueur du contexte
131K
Modalités
image, text

Radar de capacités

31
general
47
coding
68
reasoning
42
science
70
agents
90
multimodal

Classements

Domaine#RangScoreSource
Capacité agentique83
44.0
LS
Classement codage306
37.0
AA
Classement général354
37.0
AA
Classement multimodal31
56.0
LS
Science330
42.0
AA

Scores de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

3d

BLINK67.3%Aut.

Agents

BFCL-v370.2%Aut.
OSWorld32.6%Aut.

Biology

GPQANYU + Cohere + Anthropic (2023)68.9%Aut.

Chemistry

SuperGPQA54.6%Aut.

Communication

MM-MT-Bench8.40 / 100Aut.
WritingBench82.9%Aut.
Multi-IF72.0%Aut.

Creativity

Creative Writing v385.6%Aut.
Arena-Hard v264.7%Aut.

Finance

MMLU86.4%Aut.
MMLU-Pro78.6%Aut.
MMLU-ProX73.4%Aut.

General

MMLU-Redux89.8%Aut.
IFEvalGoogle Research (2023)84.7%Aut.
MLVU-M82.1%Aut.
MMStar77.7%Aut.
MMMU (val)76.0%Aut.
Include74.0%Aut.
LiveBench 2024112572.2%Aut.
MMMU-Pro65.3%Aut.
LiveCodeBench v643.8%Aut.

Grounding

ScreenSpot95.8%Aut.
ScreenSpot Pro57.9%Aut.

Image To Text

OCRBench89.5%Aut.
OCRBench-V2 (en)67.4%Aut.
OCRBench-V2 (zh)59.2%Aut.

Language

CharadesSTA61.2%Aut.

Long Context

LVBench63.8%Aut.

Math

MathVista-Mini83.8%Aut.
AIME 202566.2%Aut.
MathVision63.4%Aut.
PolyMATH40.5%Aut.

Multimodal

DocVQAtest96.9%Aut.
CharXiv-D90.5%Aut.
AI2D89.5%Aut.
InfoVQAtest87.0%Aut.
CC-OCR80.3%Aut.
MVBench72.8%Aut.
MuirBench72.8%Aut.
CharXiv-R62.8%Aut.

Reasoning

Hallusion Bench63.8%Aut.
ERQA48.8%Aut.

Spatial Reasoning

RealWorldQA79.0%Aut.

Vision

ODinW46.6%Aut.

Indices d'évaluation AA

(Artificial Analysis)
Math Index(Artificial Analysis)
68.3
Intelligence Index(Artificial Analysis)
11.0
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.8
Aime 25(MAA (Mathematical Association of America))
0.7
Gpqa(NYU + Cohere + Anthropic (2023))
0.7
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.5
Ifbench(Google Research (2023))
0.4
Lcr(Artificial Analysis)
0.3
Scicode(UIUC + Argonne National Lab (2024))
0.3
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.3
Terminalbench Hard(Stanford × Laude Institute (2026))
0.1
Hle(Center for AI Safety + Scale AI (2025))
0.1

Scores par catégorie LLM Stats

(LLM Stats (zeroeval))
Communication
3
Multimodal
1
General
90
Legal
80
Structured Output
80
Instruction Following
80
Language
80
Grounding
80
Creativity
80
Text-to-image
80
Writing
80
Math
70
Reasoning
70
Spatial Reasoning
70
Image To Text
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

Tarification

Prix d'entrée$0.7 / 1M tokens
Prix de sortie$2.8 / 1M tokens
Prix mixte (3:1)$1.225 / 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

1 fournisseurs

FournisseurEntréeSortie
1AlibabaPRINCIPAL
$0.7
$2.8

Comparer les prix entre différents fournisseurs API pour ce modèle.

Sources externes