gemgenpro/qwen3-vl-2b • LM Studio Hubqwen3-vl-2b
qwen3-vl-2b
Qwen3 VL 2B
The latest generation vision-language model in the Qwen series with comprehensive upgrades to visual perception and spatial reasoning.
Key Features
Parameters
Custom configuration options included with this model
Sources
The underlying model files this model uses
Qwen3 VL 2B
The latest generation vision-language model in the Qwen series with comprehensive upgrades to visual perception and spatial reasoning.
Key Features
Parameters
Custom configuration options included with this model
Sources
The underlying model files this model uses
Visual Agent: Operates PC and mobile GUIs—recognizes elements, understands functions, and completes tasksVisual Coding: Generates Draw.io, HTML, CSS, and JavaScript from images and videosAdvanced Spatial Perception: Provides 2D/3D grounding for spatial reasoning and embodied AI applicationsUpgraded Recognition: Recognizes celebrities, anime, products, landmarks, flora, fauna, and moreExpanded OCR: Supports 32 languages with robust performance in low light, blur, and tilt conditionsPure Text Performance: Text understanding on par with pure LLMs through seamless text-vision fusion
- 2B parameters
- DeepStack for fine-grained detail capture
- Text-Timestamp Alignment for precise event localization
- Context length: 256,000 tokens
- Vision-enabled multimodal model
Delivers strong vision-language performance across diverse tasks including document analysis, visual question answering, and agentic interactions.
Visual Agent: Operates PC and mobile GUIs—recognizes elements, understands functions, and completes tasksVisual Coding: Generates Draw.io, HTML, CSS, and JavaScript from images and videosAdvanced Spatial Perception: Provides 2D/3D grounding for spatial reasoning and embodied AI applicationsUpgraded Recognition: Recognizes celebrities, anime, products, landmarks, flora, fauna, and moreExpanded OCR: Supports 32 languages with robust performance in low light, blur, and tilt conditionsPure Text Performance: Text understanding on par with pure LLMs through seamless text-vision fusion
- 2B parameters
- DeepStack for fine-grained detail capture
- Text-Timestamp Alignment for precise event localization
- Context length: 256,000 tokens
- Vision-enabled multimodal model
Delivers strong vision-language performance across diverse tasks including document analysis, visual question answering, and agentic interactions.