Saltar al contenido principal

Qwen3 VL 30B A3B 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
2025-10-03
Parámetros
31.0B
Longitud del contexto
131K
Modalidades
image, text, video

Radar de capacidades

29
general
44
coding
72
reasoning
43
scienceest.
70
agents
100
multimodal

Science usa un proxy de razonamiento cuando los benchmarks científicos dedicados no están disponibles.

Rankings

Dominio#PosiciónPuntuaciónFuente
Capacidad agéntica80
52.0
LS
Ranking de codificación289
31.0
AA
Ranking general341
33.0
AA
Razonamiento matemático110
73.0
AA
Ranking multimodal50
75.0
LS
Razonamiento90
51.0
LS
Ciencia255
44.0
AA

Puntuaciones de benchmarks (LLM Stats)

3d

BLINK67.7%Aut.

Agents

BFCL-v366.3%Aut.
OSWorld30.3%Aut.

Biology

GPQA70.4%Aut.

Chemistry

SuperGPQA53.1%Aut.

Communication

MM-MT-Bench8.10 / 100Aut.
WritingBench82.6%Aut.
Multi-IF66.1%Aut.

Creativity

Creative Writing v384.6%Aut.
Arena-Hard v258.5%Aut.

Factuality

SimpleQA27.0%Aut.

Finance

MMLU85.0%Aut.
MMLU-Pro77.8%Aut.
MMLU-ProX70.9%Aut.

General

MMLU-Redux88.4%Aut.
IFEval85.8%Aut.
MLVU-M81.3%Aut.
MMMU (val)74.2%Aut.
MMStar72.1%Aut.
Include71.6%Aut.
LiveBench 2024112565.4%Aut.
MMMU-Pro60.4%Aut.
LiveCodeBench v642.6%Aut.

Grounding

ScreenSpot94.7%Aut.
ScreenSpot Pro60.5%Aut.

Healthcare

VideoMMMU68.7%Aut.

Image To Text

OCRBench90.3%Aut.
OCRBench-V2 (en)63.2%Aut.
OCRBench-V2 (zh)57.8%Aut.

Language

CharadesSTA63.5%Aut.

Long Context

LVBench62.5%Aut.

Math

MathVista-Mini80.1%Aut.
AIME 202569.3%Aut.
MathVision60.2%Aut.
HMMT2550.6%Aut.
PolyMATH44.3%Aut.

Multimodal

DocVQAtest95.0%Aut.
MMBench-V1.187.0%Aut.
CharXiv-D85.5%Aut.
AI2D85.0%Aut.
InfoVQAtest82.0%Aut.
CC-OCR80.7%Aut.
Video-MME74.5%Aut.
MVBench72.3%Aut.
MuirBench62.9%Aut.
CharXiv-R48.9%Aut.

Reasoning

Hallusion Bench61.5%Aut.
ERQA43.0%Aut.

Spatial Reasoning

RealWorldQA73.7%Aut.

Vision

ODinW47.5%Aut.

Índices de evaluación AA

Math Index
72.3
Intelligence Index
10.0
Mmlu Pro
0.8
Aime 25
0.7
Gpqa
0.7
Livecodebench
0.5
Ifbench
0.3
Scicode
0.3
Lcr
0.2
Tau2
0.2
Hle
0.1
Terminalbench Hard
0.1

Puntuaciones por categoría LLM Stats

Communication
3
Multimodal
100
Instruction Following
80
Language
80
Structured Output
80
Grounding
80
Creativity
80
Text-to-image
80
Writing
80
Image To Text
70
Legal
70
Math
70
Reasoning
70
Spatial Reasoning
70
Finance
70
General
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
Factuality
30

Precios

Precio de entrada$0.2 / 1M tokens
Precio de salida$0.6 / 1M tokens
Precio mixto (3:1)$0.3 / 1M tokens

Velocidad

Tokens/seg122.4
Retraso del primer token1.11s
Tiempo hasta la respuesta1.11s

Ranking de Precios por Proveedor

Ranking de Precios por Proveedor

9 proveedores

Más barato: OpenRouterMás caro: SiliconFlow
ProveedorEntradaSalida
1OpenRouterMás barato
$0.13
$1.56
2Kilo Gateway
$0.13
$1.56
3NEAR AI Cloud
$0.15
$0.55
4AlibabaPRINCIPAL
$0.2
$0.6
5NovitaAI
$0.2
$1
6LLM Gateway
$0.2
$1
7evroc
$0.24
$0.94
8SiliconFlow (China)
$0.29
$1
9SiliconFlow
$0.29
$1

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas