Passer au contenu principal

Qwen3 VL 4B (Reasoning)

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
4.0B
Longueur du contexte
Modalités
image, text

Radar de capacités

26
general
29
coding
30
reasoning
29
science
70
agents
100
multimodal

Classements

Domaine#RangScoreSource
Capacité agentique110
37.0
LS
Classement codage412
22.0
AA
Classement général429
30.0
AA
Classement multimodal85
22.0
LS
Science464
27.0
AA

Scores de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

3d

BLINK63.4%Aut.

Agents

BFCL-v367.3%Aut.
OSWorld31.4%Aut.

Biology

GPQANYU + Cohere + Anthropic (2023)64.1%Aut.

Chemistry

SuperGPQA46.8%Aut.

Communication

MM-MT-Bench7.70 / 100Aut.
WritingBench84.0%Aut.
Multi-IF73.6%Aut.

Creativity

Creative Writing v376.1%Aut.
Arena-Hard v236.8%Aut.

Finance

MMLU81.5%Aut.
MMLU-Pro73.6%Aut.
MMLU-ProX65.0%Aut.

General

MMLU-Redux86.0%Aut.
IFEvalGoogle Research (2023)82.6%Aut.
MLVU-M75.7%Aut.
MMStar73.2%Aut.
MMMU (val)70.8%Aut.
LiveBench 2024112568.4%Aut.
Include64.6%Aut.
MMMU-Pro57.0%Aut.
LiveCodeBench v651.3%Aut.

Grounding

ScreenSpot92.9%Aut.
ScreenSpot Pro49.2%Aut.

Healthcare

VideoMMMU69.4%Aut.

Image To Text

OCRBench80.8%Aut.
OCRBench-V2 (en)61.8%Aut.
OCRBench-V2 (zh)55.8%Aut.

Language

CharadesSTA59.0%Aut.

Long Context

LVBench53.5%Aut.

Math

MathVista-Mini79.5%Aut.
AIME 202574.5%Aut.
MathVision60.0%Aut.
HMMT2553.1%Aut.
PolyMATH44.6%Aut.

Multimodal

DocVQAtest94.2%Aut.
MMBench-V1.186.7%Aut.
AI2D84.9%Aut.
CharXiv-D83.9%Aut.
InfoVQAtest83.0%Aut.
MuirBench75.0%Aut.
CC-OCR73.8%Aut.
MVBench69.3%Aut.
CharXiv-R50.3%Aut.

Reasoning

Hallusion Bench64.1%Aut.
ERQA47.3%Aut.

Spatial Reasoning

RealWorldQA73.2%Aut.

Vision

ODinW39.4%Aut.

Indices d'évaluation AA

(Artificial Analysis)
Math Index(Artificial Analysis)
25.7
Intelligence Index(Artificial Analysis)
7.7
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.7
Gpqa(NYU + Cohere + Anthropic (2023))
0.5
Ifbench(Google Research (2023))
0.4
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.3
Aime 25(MAA (Mathematical Association of America))
0.3
Lcr(Artificial Analysis)
0.2
Scicode(UIUC + Argonne National Lab (2024))
0.2
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.2
Hle(Center for AI Safety + Scale AI (2025))
0.0
Terminalbench Hard(Stanford × Laude Institute (2026))
0.0

Scores par catégorie LLM Stats

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

Tarification

Prix d'entréeGratuit
Prix de sortieGratuit
Prix mixte (3:1)Gratuit

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
1DeepInfra
$0
$0

Comparer les prix entre différents fournisseurs API pour ce modèle.

Sources externes