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Model: NexaAIDev/Qwen3-VL-8B-Instruct-GGUF
Source: Original Platform

README.md

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+---
+pipeline_tag: image-text-to-text
+base_model:
+- Qwen/Qwen3-VL-8B-Instruct
+---
+# Qwen3-VL-8B-Instruct
+
+> [!NOTE]  
+> Note currently only [NexaSDK](https://github.com/NexaAI/nexa-sdk) supports this model's GGUF.
+
+Run **Qwen3-VL-8B-Instruct** optimized for CPU/GPU with [NexaSDK](https://github.com/NexaAI/nexa-sdk).
+
+## Quickstart
+
+1. **Install [NexaSDK](https://github.com/NexaAI/nexa-sdk)**
+2. Run the model locally with one line of code:
+
+   ```bash
+   nexa infer NexaAI/Qwen3-VL-8B-Instruct-GGUF
+   ```
+
+## Model Description
+**Qwen3-VL-8B-Instruct** is an 8-billion-parameter instruction-tuned multimodal large language model developed by the Qwen team at Alibaba Cloud.  
+It belongs to the **Qwen3-VL** series, designed for seamless understanding and reasoning across text, image, and video. This version combines the visual intelligence of Qwen3-VL with the instruction-following capabilities of Qwen3-LM, enabling natural, grounded conversations around complex visual content.
+
+Compared to the 4B variant, the **8B** model delivers stronger reasoning, richer context retention, and improved performance on visual and multilingual benchmarks while maintaining efficiency for deployment.
+
+## Features
+- **Enhanced Visual Understanding**: Handles complex scenes, documents, and multi-image inputs.  
+- **Instruction-Tuned Dialogue**: Produces coherent and context-aware responses aligned with user intent.  
+- **Multilingual Support**: Capable of understanding and generating in multiple languages.  
+- **Extended Context Window**: Supports longer text and multimodal contexts for better reasoning continuity.  
+- **Optimized Performance**: Balances large-scale reasoning capability with deployability for high-end edge or server environments.
+
+## Use Cases
+- Visual chatbots and multimodal assistants  
+- Document and chart interpretation  
+- Image-grounded content generation and summarization  
+- Video frame reasoning and analysis  
+- Multilingual multimodal tutoring or knowledge assistants  
+
+## Inputs and Outputs
+**Input:**
+- Text, images, or combined multimodal prompts  
+- Optional video frames or sequential image sets  
+
+**Output:**
+- Natural-language answers, summaries, captions, or structured reasoning outputs  
+- Can provide visual explanations or reasoning narratives when prompted  
+
+## License
+See the [official Qwen license](https://huggingface.co/Qwen) for details on usage and redistribution.