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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
33
coding
30
reasoning
30
science
70
agents
100
multimodal

Rankings

Dominio#PosiciónPuntuaciónFuente
Ranking de codificación517
19.0
AA
Ranking general468
30.0
AA
Ranking multimodal129
35.0
LS
Ciencia563
21.0
AA

Puntuaciones de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Chat

MM-MT-Bench7.70 / 100Aut.
IFEvalGoogle Research (2023)83.7%Aut.
Multi-IF75.1%Aut.

General

MMLU80.7%Aut.
MLVU-M78.1%Aut.
Include67.0%Aut.
BFCL-v366.3%Aut.

Language

MMLU-Redux84.9%Aut.
MMLU-Pro71.6%Aut.
MMLU-ProX65.4%Aut.

Math

MathVista-Mini77.2%Aut.
LiveBench 2024112562.0%Aut.
MathVision53.9%Aut.
AIME 202545.9%Aut.
HMMT2532.5%Aut.
PolyMATH30.4%Aut.

Multimodal

Video-MME71.4%Aut.
VideoMMMU65.3%Aut.
OSWorld33.9%Aut.

Reasoning

CharXiv-D83.0%Aut.
CharXiv-R46.4%Aut.
SuperGPQA44.5%Aut.
LiveCodeBench v639.3%Aut.

Video

CharadesSTA56.0%Aut.

Vision

DocVQAtest96.1%Aut.
ScreenSpot94.4%Aut.
OCRBench89.6%Aut.
AI2D85.7%Aut.
MMBench-V1.185.0%Aut.
InfoVQAtest83.1%Aut.
CC-OCR79.9%Aut.
RealWorldQA71.5%Aut.
MMStar70.9%Aut.
MMMU (val)69.6%Aut.
BLINK69.1%Aut.
MVBench68.7%Aut.
OCRBench-V2 (en)65.4%Aut.
MuirBench64.4%Aut.
OCRBench-V2 (zh)61.2%Aut.
Hallusion Bench61.1%Aut.
LVBench58.0%Aut.
MMMU-Pro55.9%Aut.
ScreenSpot Pro54.6%Aut.
ERQA45.8%Aut.
ODinW44.7%Aut.

Writing

WritingBench83.1%Aut.

Índices de evaluación AA

(Artificial Analysis)
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
68.6
Gpqa(NYU + Cohere + Anthropic (2023))
42.7
Livecodebench(UC Berkeley + MIT + Cornell (2024))
33.2
Ifbench(Google Research (2023))
32.3
Tau2(Sierra + U Toronto + Vector Institute (2025))
29.2
Aime 25(MAA (Mathematical Association of America))
27.3
Math Index(Artificial Analysis)
27.3
Lcr(Artificial Analysis)
16.7
Intelligence Index(Artificial Analysis)
7.3
Hle(Center for AI Safety + Scale AI (2025))
2.7
Terminalbench Hard(Stanford × Laude Institute (2026))
2.3

Puntuaciones por categoría LLM Stats

(LLM Stats (zeroeval))
Chat
3
Communication
3
Multimodal
100
Instruction Following
80
Structured Output
80
General
80
Creativity
80
Text-to-image
80
Writing
80
Image To Text
70
Language
70
Legal
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

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Fuentes externas