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Qwen3 VL 32B Instruct

AlibabaQwenOpen WeightApache 2.0 · Uso Comercial

Descripción

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.

Fecha de lanzamiento
2025-10-21
Parámetros
33.0B
Longitud del contexto
131K
Modalidades
image, text

Radar de capacidades

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

Rankings

Dominio#PosiciónPuntuaciónFuente
Capacidad agéntica83
44.0
LS
Ranking de codificación306
37.0
AA
Ranking general354
37.0
AA
Ranking multimodal31
56.0
LS
Ciencia330
42.0
AA

Puntuaciones 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.

Índices de evaluación 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

Puntuaciones por categoría 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

Precios

Precio de entrada$0.7 / 1M tokens
Precio de salida$2.8 / 1M tokens
Precio mixto (3:1)$1.225 / 1M tokens

Velocidad

Tokens/seg0.0
Retraso del primer token0.00s
Tiempo hasta la respuesta0.00s

Ranking de Precios por Proveedor

Ranking de Precios por Proveedor

1 proveedores

ProveedorEntradaSalida
1AlibabaPRINCIPAL
$0.7
$2.8

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas