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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
262K
Modalidades
image, text, video

Radar de capacidades

28
general
48
coding
72
reasoning
50
science
70
agents
100
multimodal

Rankings

Dominio#PosiciónPuntuaciónFuente
Ranking de codificación430
31.0
AA
Ranking general467
30.0
AA
Ranking multimodal120
38.0
LS
Ciencia387
39.0
AA

Puntuaciones de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Chat

MM-MT-Bench8.10 / 100Aut.
IFEvalGoogle Research (2023)85.8%Aut.
Multi-IF66.1%Aut.

Creativity

Creative Writing v384.6%Aut.

Factuality

SimpleQA27.0%Aut.

General

MMLU85.0%Aut.
MLVU-M81.3%Aut.
Include71.6%Aut.
BFCL-v366.3%Aut.
Arena-Hard v258.5%Aut.

Language

MMLU-Redux88.4%Aut.
MMLU-Pro77.8%Aut.
MMLU-ProX70.9%Aut.

Math

MathVista-Mini80.1%Aut.
AIME 202569.3%Aut.
LiveBench 2024112565.4%Aut.
MathVision60.2%Aut.
HMMT2550.6%Aut.
PolyMATH44.3%Aut.

Multimodal

Video-MME74.5%Aut.
VideoMMMU68.7%Aut.
OSWorld30.3%Aut.

Reasoning

CharXiv-D85.5%Aut.
GPQANYU + Cohere + Anthropic (2023)70.4%Aut.
SuperGPQA53.1%Aut.
CharXiv-R48.9%Aut.
LiveCodeBench v642.6%Aut.

Video

CharadesSTA63.5%Aut.

Vision

DocVQAtest95.0%Aut.
ScreenSpot94.7%Aut.
OCRBench90.3%Aut.
MMBench-V1.187.0%Aut.
AI2D85.0%Aut.
InfoVQAtest82.0%Aut.
CC-OCR80.7%Aut.
MMMU (val)74.2%Aut.
RealWorldQA73.7%Aut.
MVBench72.3%Aut.
MMStar72.1%Aut.
BLINK67.7%Aut.
OCRBench-V2 (en)63.2%Aut.
MuirBench62.9%Aut.
LVBench62.5%Aut.
Hallusion Bench61.5%Aut.
ScreenSpot Pro60.5%Aut.
MMMU-Pro60.4%Aut.
OCRBench-V2 (zh)57.8%Aut.
ODinW47.5%Aut.
ERQA43.0%Aut.

Writing

WritingBench82.6%Aut.

Índices de evaluación AA

(Artificial Analysis)
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
76.4
Aime 25(MAA (Mathematical Association of America))
72.3
Math Index(Artificial Analysis)
72.3
Gpqa(NYU + Cohere + Anthropic (2023))
69.5
Livecodebench(UC Berkeley + MIT + Cornell (2024))
47.6
Ifbench(Google Research (2023))
33.1
Tau2(Sierra + U Toronto + Vector Institute (2025))
19.0
Intelligence Index(Artificial Analysis)
7.9
Hle(Center for AI Safety + Scale AI (2025))
6.3
Terminalbench Hard(Stanford × Laude Institute (2026))
6.1

Puntuaciones por categoría LLM Stats

(LLM Stats (zeroeval))
Chat
3
Communication
3
Multimodal
100
Instruction Following
80
Language
80
Structured Output
80
General
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
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$0.8 / 1M tokens
Precio mixto (3:1)$0.35 / 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

6 proveedores

Más barato: DeepInfraMás caro: NovitaAI
ProveedorEntradaSalida
1DeepInfraMás barato
$0
$0
2Kilo Gateway
$0.13
$0.52
3OpenRouter
$0.15
$0.6
4DevPass (LLM Gateway)
$0.15
$0.6
5AlibabaPRINCIPAL
$0.2
$0.8
6NovitaAI
$0.2
$0.7

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas