Qwen3-VL Cookbooks – Multimodal Task Development Guide Released by Alibaba

What is Qwen3-VL Cookbooks？

Qwen3-VL Cookbooks is a collection of practical development guides released by Alibaba for the Qwen3-VL multimodal model, designed to help users quickly master and apply the model’s diverse capabilities. The collection includes a wide range of examples demonstrating abilities such as object recognition, document parsing, video understanding, spatial reasoning, and multimodal coding.
Each cookbook provides detailed code samples and step-by-step instructions, enabling users to learn how to apply the Qwen3-VL model effectively in real-world scenarios and fully leverage its powerful vision-language capabilities.

Main Functions of Qwen3-VL Cookbooks

• Comprehensive Operation Guides:
  Helps users quickly learn how to use the Qwen3-VL model for various multimodal tasks.

• Demonstrates Multimodal Task Implementation:
  Offers practical examples on combining image, video, and text data for task completion.

• Optimized Workflow Design:
  Provides efficient workflows and code examples to improve development and deployment efficiency.

• Supports Diverse Application Scenarios:
  Covers a wide range of use cases—from object recognition to document parsing and video understanding—to meet various needs.

• Performance Optimization Tips:
  Offers guidance for optimizing model performance according to task requirements, improving inference speed and efficiency.

Contents of Qwen3-VL Cookbooks

• Omni Recognition:
  Identifies various objects such as animals, plants, people, landmarks, and consumer goods.

• Powerful Document Parsing Capabilities:
  Extracts text and layout information from documents, supporting the Qwen HTML format.

• Precise Object Grounding Across Formats:
  Locates targets in images using relative coordinates, supporting both bounding boxes and point annotations.

• General OCR and Key Information Extraction:
  Supports OCR in 32 languages, capable of reading text under low light, blurred, or tilted conditions.

• Video Understanding:
  Performs video OCR and long-form video comprehension, enabling detailed video content analysis.

• Mobile Agent:
  Uses visual reasoning and positioning to control smartphone operations.

• Computer-Use Agent:
  Employs visual reasoning to control computer and web-based interactions.

• 3D Grounding:
  Provides accurate 3D bounding boxes for indoor and outdoor objects.

• Thinking with Images:
  Enhances image reasoning through zooming and image search tools.

• MultiModal Coding:
  Generates HTML, CSS, and JS code from image or video inputs.

• Long Document Understanding:
  Enables semantic comprehension of ultra-long documents.

• Spatial Understanding:
  Observes, interprets, and reasons about spatial relationships in images and scenes.

Project Repository

• GitHub: https://github.com/QwenLM/Qwen3-VL/tree/main/cookbooks

Application Scenarios of Qwen3-VL Cookbooks

• Object Recognition:
  Enhances smart security systems by quickly identifying suspicious individuals or objects in surveillance footage.

• Document Parsing:
  In the financial industry, automatically extracts key clauses and data from contracts, improving audit efficiency.

• Precise Object Grounding:
  In autonomous driving, accurately detects and localizes road signs and obstacles to ensure driving safety.

• Multilingual OCR and Key Information Extraction:
  In intelligent customer service, reads and extracts key information from multilingual user documents to enhance service efficiency.

• Video Understanding:
  In the education sector, automatically generates subtitles for online course videos, facilitating student learning.