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--- |
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pipeline_tag: image-text-to-text |
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base_model: |
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- Qwen/Qwen3-VL-8B-Instruct |
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tags: |
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- mlx |
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--- |
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# Qwen3-VL-8B-Instruct |
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Run **Qwen3-VL-8B-Instruct** optimized for **Apple Silicon** on MLX with [NexaSDK](https://github.com/NexaAI/nexa-sdk). |
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## Quickstart |
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1. **Install [NexaSDK](https://github.com/NexaAI/nexa-sdk)** |
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2. Run the model locally with one line of code: |
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```bash |
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nexa infer NexaAI/qwen3vl-8B-Instruct-4bit-mlx |
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``` |
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## Model Description |
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**Qwen3-VL-8B-Instruct** is an 8-billion-parameter instruction-tuned multimodal large language model developed by the Qwen team at Alibaba Cloud. |
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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. |
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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. |
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## Features |
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- **Enhanced Visual Understanding**: Handles complex scenes, documents, and multi-image inputs. |
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- **Instruction-Tuned Dialogue**: Produces coherent and context-aware responses aligned with user intent. |
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- **Multilingual Support**: Capable of understanding and generating in multiple languages. |
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- **Extended Context Window**: Supports longer text and multimodal contexts for better reasoning continuity. |
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- **Optimized Performance**: Balances large-scale reasoning capability with deployability for high-end edge or server environments. |
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## Use Cases |
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- Visual chatbots and multimodal assistants |
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- Document and chart interpretation |
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- Image-grounded content generation and summarization |
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- Video frame reasoning and analysis |
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- Multilingual multimodal tutoring or knowledge assistants |
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## Inputs and Outputs |
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**Input:** |
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- Text, images, or combined multimodal prompts |
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- Optional video frames or sequential image sets |
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**Output:** |
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- Natural-language answers, summaries, captions, or structured reasoning outputs |
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- Can provide visual explanations or reasoning narratives when prompted |
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## License |
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See the [official Qwen license](https://huggingface.co/Qwen) for details on usage and redistribution. |
