Qwen3-VL-235B-A22B-Instruct

Description

Qwen3-VL-235B-A22B-Instruct is a cutting-edge vision-language model in the Qwen series, designed to deliver comprehensive upgrades in text understanding and generation, visual perception, and reasoning capabilities. It offers enhanced spatial and video dynamics comprehension, extended context length, and stronger agent interaction capabilities. The model is available in Dense and MoE architectures, allowing for scalable deployment from edge to cloud. It includes Instruct and reasoning-enhanced Thinking editions for flexible, on-demand deployment.

Key enhancements of Qwen3-VL-235B-A22B-Instruct include its ability to operate PC/mobile GUIs, recognize elements, understand functions, invoke tools, and complete tasks. It features a Visual Coding Boost that generates Draw.io/HTML/CSS/JS from images and videos. Its advanced spatial perception allows it to judge object positions, viewpoints, and occlusions, providing stronger 2D grounding and enabling 3D grounding for spatial reasoning and embodied AI.

The model supports a native 256K context, expandable to 1M, enabling it to handle books and hours-long videos with full recall and second-level indexing. Its enhanced multimodal reasoning excels in STEM/Math, offering causal analysis and logical, evidence-based answers. The upgraded visual recognition is capable of recognizing a wide range of entities, including celebrities, anime, products, landmarks, flora, and fauna.

Qwen3-VL-235B-A22B-Instruct also features expanded OCR capabilities, supporting 32 languages and improving performance in low light, blur, and tilt conditions. It offers better handling of rare and ancient characters and jargon, along with improved long-document structure parsing. The model's text understanding is on par with pure LLMs, providing seamless text-vision fusion for lossless, unified comprehension.

Qwen3-VL-235B-A22B-Instruct Highlights

• Superior text understanding and generation

• Enhanced visual perception and reasoning

• Extended context length up to 1M

• Flexible deployment in Dense and MoE architectures

• Visual Coding Boost for HTML/CSS/JS generation

• Advanced spatial perception for 2D and 3D grounding

• Multimodal reasoning excelling in STEM/Math

• Upgraded visual recognition across diverse entities

• Expanded OCR supporting 32 languages

• Seamless text-vision fusion

Getting Started with Qwen3-VL-235B-A22B-Instruct

1. 1

   Access page: Visit Hugging Face model repository

2. 2

   Load model: Download Qwen3-VL-235B-A22B-Instruct

3. 3

   Configure environment: Set up necessary dependencies

4. 4

   Integrate: Use with 🤗 Transformers or ModelScope

5. 5

   Fine-tune: Customize model for specific tasks

Qwen3-VL-235B-A22B-Instruct's Use Cases

• Visual coding
• Spatial reasoning
• Multimodal STEM analysis
• Extended context processing
• OCR in challenging conditions

FAQ from Qwen3-VL-235B-A22B-Instruct

• What is Qwen3-VL-235B-A22B-Instruct?

  It is a vision-language model offering advanced text and visual understanding capabilities.

• How does Qwen3-VL enhance visual coding?

  It generates Draw.io/HTML/CSS/JS from images and videos.

• What languages does the expanded OCR support?

  The OCR supports 32 languages, improving performance in challenging conditions.

• What are the deployment options for Qwen3-VL?

  It is available in Dense and MoE architectures for flexible deployment.

• How does Qwen3-VL handle long context?

  It supports a native 256K context, expandable to 1M for handling extensive content.

• What is the Visual Agent feature?

  It operates PC/mobile GUIs, recognizing elements and completing tasks.

• How does Qwen3-VL excel in STEM/Math?

  It offers causal analysis and logical, evidence-based answers.

• What is the model's visual recognition capability?

  It recognizes a wide range of entities, including celebrities and landmarks.