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Qwen3 VL 30B A3B Instruct

AlibabaQwen오픈 웨이트Apache 2.0 · 상업적 사용 가능

설명

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.

출시일
2025-10-03
파라미터
31.0B
컨텍스트 길이
262K
모달리티
image, text, video

능력 레이더

29
general
44
coding
72
reasoning
43
science
70
agents
100
multimodal

랭킹

도메인#순위점수소스
에이전트형 역량126
33.0
LS
코딩 랭킹336
31.0
AA
종합 랭킹398
32.0
AA
멀티모달 랭킹72
34.0
LS
과학304
44.0
AA

벤치마크 점수 (LLM Stats)

(LLM Stats (zeroeval))

3d

BLINK67.7%자체 보고

Agents

BFCL-v366.3%자체 보고
OSWorld30.3%자체 보고

Biology

GPQANYU + Cohere + Anthropic (2023)70.4%자체 보고

Chemistry

SuperGPQA53.1%자체 보고

Communication

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

Creativity

Creative Writing v384.6%자체 보고
Arena-Hard v258.5%자체 보고

Factuality

SimpleQA27.0%자체 보고

Finance

MMLU85.0%자체 보고
MMLU-Pro77.8%자체 보고
MMLU-ProX70.9%자체 보고

General

MMLU-Redux88.4%자체 보고
IFEvalGoogle Research (2023)85.8%자체 보고
MLVU-M81.3%자체 보고
MMMU (val)74.2%자체 보고
MMStar72.1%자체 보고
Include71.6%자체 보고
LiveBench 2024112565.4%자체 보고
MMMU-Pro60.4%자체 보고
LiveCodeBench v642.6%자체 보고

Grounding

ScreenSpot94.7%자체 보고
ScreenSpot Pro60.5%자체 보고

Healthcare

VideoMMMU68.7%자체 보고

Image To Text

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

Language

CharadesSTA63.5%자체 보고

Long Context

LVBench62.5%자체 보고

Math

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

Multimodal

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

Reasoning

Hallusion Bench61.5%자체 보고
ERQA43.0%자체 보고

Spatial Reasoning

RealWorldQA73.7%자체 보고

Vision

ODinW47.5%자체 보고

AA 평가 지수

(Artificial Analysis)
Math Index(Artificial Analysis)
72.3
Intelligence Index(Artificial Analysis)
9.9
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))
0.3
Scicode(UIUC + Argonne National Lab (2024))
0.3
Lcr(Artificial Analysis)
0.3
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.2
Hle(Center for AI Safety + Scale AI (2025))
0.1
Terminalbench Hard(Stanford × Laude Institute (2026))
0.1

LLM Stats 카테고리 점수

(LLM Stats (zeroeval))
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

가격

입력 가격$0.2 / 1M 토큰
출력 가격$0.8 / 1M 토큰
혼합 가격 (3:1)$0.35 / 1M 토큰

속도

토큰/초0.0
첫 토큰 지연0.00s
첫 응답 지연0.00s

공급자 가격 순위

공급자 가격 순위

5개 공급자

최저가: Kilo Gateway최고가: NovitaAI
공급자입력출력
1Kilo Gateway최저가
$0.13
$0.52
2OpenRouter
$0.15
$0.6
3LLM Gateway
$0.15
$0.6
4Alibaba주요
$0.2
$0.8
5NovitaAI
$0.2
$0.7

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