Qwen 2.5-VL

The Open Vision-Reasoner: SOTA Multimodal Performance

Qwen 2.5-VL is Alibaba's state-of-the-art open-weight multimodal model, designed to bridge the gap between open source and proprietary vision-language models. It features advanced 'NaViVi' (Native Dynamic Resolution) architecture, allowing it to process images of any resolution and videos of any length with extreme precision. It excels at complex visual reasoning, document understanding (OCR), and real-time video analysis, matching or exceeding GPT-4o in many multimodal benchmarks while remaining fully open for the community to build upon.

QUICK TIPS

1 Use the 72B model for maximum reasoning depth and the 7B model for real-time speed

2 Leverage the dynamic resolution by providing high-quality images for dense OCR tasks

3 Provide timestamps when asking questions about long videos to get more precise answers

4 Combine with tools like LangChain to build visual agents that can navigate UIs

5 Check the Hugging Face community for quantized versions to run on consumer GPUs

RESOURCES & SETUP

Qwen 2.5-VL GitHub ↗

Access the source code, training details, and deployment guides.

Local Deployment Guide ↗

How to run Qwen 2.5-VL on your own hardware with vLLM.

SIMILAR TOOLS

Claude Opus 4.6 NotebookLM Grok DeepSeek Llama

USE CASE EXAMPLES

Complex Document Digitization

Extracting structured data from multi-page PDFs with complex tables and charts.

STEPS:

Upload the document images or PDF pages
Ask: 'Extract all table data into a JSON format'
Review the high-precision OCR output

Visual UI Automation

Using the model to 'see' a website or app UI and describe the steps to complete a task.

STEPS:

Provide a screenshot of the UI
Ask: 'Where should I click to change the notification settings?'
Get the exact coordinates and visual description of the element

PRICING

Free Completely free

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FREQUENTLY ASKED QUESTIONS

Is Qwen 2.5-VL free?

Yes, Qwen 2.5-VL is completely free to use with no paid tiers or limitations.

What can I do with Qwen 2.5-VL?

Qwen 2.5-VL is designed for High-precision OCR and document analysis, Long-form video understanding and summarization, Building custom multimodal agents with open weights. Qwen 2. Key strengths include Native Dynamic Resolution: Processes images without resizing or quality loss and SOTA Video Understanding: Analyzes videos over 1 hour in length.

How do I use Qwen 2.5-VL?

Qwen 2.5-VL is a large language model for text generation, analysis, and conversation. Access through the web interface. Enter prompts or questions to get responses. It excels at native dynamic resolution: processes images without resizing or quality loss.

How do I get started with Qwen 2.5-VL?

Try Qwen 2.5-VL for free on the Qwen official demo site or Hugging Face Spaces. For developers, download the weights from Hugging Face and run them locally using vLLM or Ollama. API access is available through providers like DashScope and OpenRouter.

Is Qwen 2.5-VL open source?

Yes, Qwen 2.5-VL is open source. You can access the source code on GitHub at https://github.com/QwenLM/Qwen2.5-VL, contribute to development, and deploy it on your own infrastructure.