Saltar al contenido principal

Qwen3 VL 8B 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
2025-10-14
Parámetros
9.0B
Longitud del contexto
262K
Modalidades
image, text, video

Radar de capacidades

25
general
30
coding
30
reasoning
26
science
70
agents
100
multimodal

Rankings

Dominio#PosiciónPuntuaciónFuente
Capacidad agéntica102
38.0
LS
Ranking de codificación419
20.0
AA
Ranking general407
31.0
AA
Ranking multimodal68
36.0
LS
Ciencia473
24.0
AA

Puntuaciones de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

3d

BLINK69.1%Aut.

Agents

BFCL-v366.3%Aut.
OSWorld33.9%Aut.

Chemistry

SuperGPQA44.5%Aut.

Communication

MM-MT-Bench7.70 / 100Aut.
WritingBench83.1%Aut.
Multi-IF75.1%Aut.

Finance

MMLU80.7%Aut.
MMLU-Pro71.6%Aut.
MMLU-ProX65.4%Aut.

General

MMLU-Redux84.9%Aut.
IFEvalGoogle Research (2023)83.7%Aut.
MLVU-M78.1%Aut.
MMStar70.9%Aut.
MMMU (val)69.6%Aut.
Include67.0%Aut.
LiveBench 2024112562.0%Aut.
MMMU-Pro55.9%Aut.
LiveCodeBench v639.3%Aut.

Grounding

ScreenSpot94.4%Aut.
ScreenSpot Pro54.6%Aut.

Healthcare

VideoMMMU65.3%Aut.

Image To Text

OCRBench89.6%Aut.
OCRBench-V2 (en)65.4%Aut.
OCRBench-V2 (zh)61.2%Aut.

Language

CharadesSTA56.0%Aut.

Long Context

LVBench58.0%Aut.

Math

MathVista-Mini77.2%Aut.
MathVision53.9%Aut.
AIME 202545.9%Aut.
HMMT2532.5%Aut.
PolyMATH30.4%Aut.

Multimodal

DocVQAtest96.1%Aut.
AI2D85.7%Aut.
MMBench-V1.185.0%Aut.
InfoVQAtest83.1%Aut.
CharXiv-D83.0%Aut.
CC-OCR79.9%Aut.
Video-MME71.4%Aut.
MVBench68.7%Aut.
MuirBench64.4%Aut.
CharXiv-R46.4%Aut.

Reasoning

Hallusion Bench61.1%Aut.
ERQA45.8%Aut.

Spatial Reasoning

RealWorldQA71.5%Aut.

Vision

ODinW44.7%Aut.

Índices de evaluación AA

(Artificial Analysis)
Math Index(Artificial Analysis)
27.3
Intelligence Index(Artificial Analysis)
8.2
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.7
Gpqa(NYU + Cohere + Anthropic (2023))
0.4
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.3
Ifbench(Google Research (2023))
0.3
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.3
Aime 25(MAA (Mathematical Association of America))
0.3
Scicode(UIUC + Argonne National Lab (2024))
0.2
Lcr(Artificial Analysis)
0.2
Hle(Center for AI Safety + Scale AI (2025))
0.0
Terminalbench Hard(Stanford × Laude Institute (2026))
0.0

Puntuaciones por categoría LLM Stats

(LLM Stats (zeroeval))
Communication
3
Multimodal
100
Structured Output
80
Instruction Following
80
General
80
Creativity
80
Text-to-image
80
Writing
80
Legal
70
Image To Text
70
Language
70
Finance
70
Grounding
70
Healthcare
70
3d
70
Tool Calling
70
Vision
70
Long Context
60
Math
60
Reasoning
60
Spatial Reasoning
60
Video
60
Agents
50
Physics
40
Chemistry
40
Economics
40

Precios

Precio de entrada$0.18 / 1M tokens
Precio de salida$0.7 / 1M tokens
Precio mixto (3:1)$0.31 / 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

4 proveedores

Más barato: NovitaAIMás caro: Alibaba
ProveedorEntradaSalida
1NovitaAIMás barato
$0.08
$0.5
2OpenRouter
$0.117
$0.455
3Kilo Gateway
$0.117
$0.455
4AlibabaPRINCIPAL
$0.18
$0.7

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas