---
base_model:
- Qwen/Qwen3-VL-2B-Instruct
tags:
- GGUF
---
# Qwen3-VL-2B-Instruct

Currently, only [NexaSDK](https://github.com/NexaAI/nexa-sdk) supports this GGUF.

## Quickstart:
- Download [NexaSDK](https://github.com/NexaAI/nexa-sdk) with one click
- one line of code to run in your terminal:
```
nexa infer NexaAI/Qwen3-VL-2B-Instruct-GGUF
```

## Model Description
**Qwen3-VL-2B-Instruct** is a 2-billion-parameter, instruction-tuned vision-language model in the Qwen3-VL family. It’s designed for efficient multimodal understanding and generation—combining strong text skills with image and video perception—making it ideal for edge and on-device deployment. It supports long contexts (up to 256K tokens) and features upgraded architecture for better spatial, visual, and temporal reasoning.

## Features
- **Multimodal I/O**: Understands images and long videos, performs OCR, and handles mixed image-text prompts.  
- **Long-context reasoning**: Up to 256K context for books, documents, or extended visual analysis.  
- **Spatial & temporal understanding**: Improved grounding and temporal event tracking for videos.  
- **Agentic capabilities**: Recognizes UI elements and reasons about screen layouts for tool use.  
- **Lightweight footprint**: 2B parameters for efficient inference across CPU, GPU, or NPU.  

## Use Cases
- Visual question answering, captioning, and summarization  
- OCR and document understanding (multi-page, multilingual)  
- Video analysis and highlight detection  
- On-device visual assistants and UI automation agents  
- Edge analytics and lightweight IoT vision tasks  

## Inputs and Outputs
**Inputs**
- Text prompts  
- Images (single or multiple)  
- Videos or frame sequences  
- Mixed multimodal chat turns  

**Outputs**
- Natural language answers, captions, and visual reasoning  
- OCR text and structured visual information  

## License
This model is released under the **Apache 2.0 License**.  
Please refer to the Hugging Face model card for detailed licensing and usage information.