NexaAI/Qwen3-VL-4B-Thinking-GGUF

Qwen3-VL-4B-Thinking

Run Qwen3-VL-4B-Thinking optimized for CPU/GPU with NexaSDK.

Quickstart

1. Install NexaSDK

2. Run the model locally with one line of code:

   nexa infer NexaAI/Qwen3-VL-4B-Thinking-GGUF
   

Model Description

Qwen3-VL-4B-Thinking is a 4-billion-parameter multimodal large language model from the Qwen team at Alibaba Cloud.
Part of the Qwen3-VL (Vision-Language) family, it is designed for advanced visual reasoning and chain-of-thought generation across image, text, and video inputs.

Compared to the Instruct variant, the Thinking model emphasizes deeper multi-step reasoning, analysis, and planning. It produces detailed, structured outputs that reflect intermediate reasoning steps, making it well-suited for research, multimodal understanding, and agentic workflows.

Features

• Vision-Language Understanding: Processes images, text, and videos for joint reasoning tasks.
• Structured Thinking Mode: Generates intermediate reasoning traces for better transparency and interpretability.
• High Accuracy on Visual QA: Performs strongly on visual question answering, chart reasoning, and document analysis benchmarks.
• Multilingual Support: Understands and responds in multiple languages.
• Optimized for Efficiency: Delivers strong performance at 4B scale for on-device or edge deployment.

Use Cases

• Multimodal reasoning and visual question answering
• Scientific and analytical reasoning tasks involving charts, tables, and documents
• Step-by-step visual explanation or tutoring
• Research on interpretability and chain-of-thought modeling
• Integration into agent systems that require structured reasoning

Inputs and Outputs

Input:

• Text, images, or combined multimodal prompts (e.g., image + question)

Output:

• Generated text, reasoning traces, or structured responses
• May include explicit thought steps or structured JSON reasoning sequences

License

Check the official Qwen license for terms of use and redistribution.