> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/QwenLM/Qwen3-VL/llms.txt
> Use this file to discover all available pages before exploring further.

# Model Cards

> Complete overview of all Qwen3-VL model variants with download links

## Available Models

Qwen3-VL is available in multiple sizes and architectures to suit different deployment scenarios, from edge devices to cloud infrastructure.

### Model Architectures

* **Dense Models**: Traditional transformer architecture
* **MoE (Mixture of Experts)**: Sparse architecture for efficient scaling
* **Instruct Editions**: Fine-tuned for instruction following
* **Thinking Editions**: Enhanced with reasoning capabilities

## Dense Models

### Qwen3-VL-2B

**Instruct Edition**

* HuggingFace: [Qwen/Qwen3-VL-2B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-2B-Instruct)
* ModelScope: Available in [Qwen3-VL Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)
* Released: October 21, 2025

**Thinking Edition**

* HuggingFace: [Qwen/Qwen3-VL-2B-Thinking](https://huggingface.co/Qwen/Qwen3-VL-2B-Thinking)
* ModelScope: Available in [Qwen3-VL Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)
* Released: October 21, 2025

### Qwen3-VL-4B

**Instruct Edition**

* HuggingFace: [Qwen/Qwen3-VL-4B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct)
* ModelScope: Available in [Qwen3-VL Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)
* Released: October 15, 2025

**Thinking Edition**

* HuggingFace: [Qwen/Qwen3-VL-4B-Thinking](https://huggingface.co/Qwen/Qwen3-VL-4B-Thinking)
* ModelScope: Available in [Qwen3-VL Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)
* Released: October 15, 2025

### Qwen3-VL-8B

**Instruct Edition**

* HuggingFace: [Qwen/Qwen3-VL-8B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct)
* ModelScope: Available in [Qwen3-VL Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)
* Released: October 15, 2025

**Thinking Edition**

* HuggingFace: [Qwen/Qwen3-VL-8B-Thinking](https://huggingface.co/Qwen/Qwen3-VL-8B-Thinking)
* ModelScope: Available in [Qwen3-VL Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)
* Released: October 15, 2025

### Qwen3-VL-32B

**Instruct Edition**

* HuggingFace: [Qwen/Qwen3-VL-32B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-32B-Instruct)
* ModelScope: Available in [Qwen3-VL Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)
* Released: October 21, 2025

**Thinking Edition**

* HuggingFace: [Qwen/Qwen3-VL-32B-Thinking](https://huggingface.co/Qwen/Qwen3-VL-32B-Thinking)
* ModelScope: Available in [Qwen3-VL Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)
* Released: October 21, 2025

## MoE Models

### Qwen3-VL-30B-A3B

**Architecture**: 30B total parameters, 3B active per token

**Instruct Edition**

* HuggingFace: [Qwen/Qwen3-VL-30B-A3B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct)
* ModelScope: Available in [Qwen3-VL Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)
* Released: October 4, 2025

**Thinking Edition**

* HuggingFace: [Qwen/Qwen3-VL-30B-A3B-Thinking](https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Thinking)
* ModelScope: Available in [Qwen3-VL Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)
* Released: October 4, 2025

### Qwen3-VL-235B-A22B

**Architecture**: 235B total parameters, 22B active per token

**Instruct Edition**

* HuggingFace: [Qwen/Qwen3-VL-235B-A22B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Instruct)
* ModelScope: Available in [Qwen3-VL Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)
* Released: September 23, 2025

**Thinking Edition**

* HuggingFace: [Qwen/Qwen3-VL-235B-A22B-Thinking](https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Thinking)
* ModelScope: Available in [Qwen3-VL Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)
* Released: September 23, 2025

**FP8 Quantized Version**

* HuggingFace: [Qwen/Qwen3-VL-235B-A22B-Instruct-FP8](https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Instruct-FP8)
* For efficient deployment on H100/H200 GPUs

## Collections

### HuggingFace Collection

All Qwen3-VL models including FP8 quantized versions:

* [Qwen3-VL Collection](https://huggingface.co/collections/Qwen/qwen3-vl-68d2a7c1b8a8afce4ebd2dbe)

### ModelScope Collection

All Qwen3-VL models for users in mainland China:

* [Qwen3-VL Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)

## Quantized Models

### FP8 Versions

FP8 quantized models are available for all major model sizes, optimized for deployment on NVIDIA H100+ GPUs with CUDA 12+.

Find all FP8 versions in:

* [HuggingFace Collection](https://huggingface.co/collections/Qwen/qwen3-vl-68d2a7c1b8a8afce4ebd2dbe)
* [ModelScope Collection](https://modelscope.cn/collections/Qwen3-VL-5c7a94c8cb144b)

## Legacy Models

### Qwen2.5-VL Series

**Qwen2.5-VL-32B-Instruct**

* HuggingFace: [Qwen/Qwen2.5-VL-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-32B-Instruct)
* Released: March 25, 2025

**Other Qwen2.5-VL models**: 3B, 7B, 72B

* Collection: [Qwen2.5-VL](https://huggingface.co/collections/Qwen/qwen2-vl-66cee7455501d7126940800d)
* Released: January 28, 2025

**AWQ Quantized Versions**: Available for 3B, 7B, and 72B models

### Qwen2-VL Series

**Qwen2-VL-72B-Instruct**

* HuggingFace: [Qwen/Qwen2-VL-72B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-72B-Instruct)
* Quantized: AWQ, GPTQ-Int4, GPTQ-Int8
* Released: September 19, 2024

**Other sizes**: 2B, 7B

* Released: August 30, 2024

### QvQ-72B-Preview

Experimental research model focusing on visual reasoning:

* HuggingFace: [Qwen/QVQ-72B-Preview](https://huggingface.co/Qwen/QVQ-72B-Preview)
* Released: December 25, 2024

## Model Selection Guide

### By Use Case

**Edge Deployment**: Qwen3-VL-2B (Instruct/Thinking)

* Smallest footprint, suitable for mobile and edge devices

**Balanced Performance**: Qwen3-VL-4B or Qwen3-VL-8B

* Good balance between performance and resource requirements

**High Performance**: Qwen3-VL-32B or Qwen3-VL-30B-A3B

* Strong performance for demanding applications

**Maximum Capability**: Qwen3-VL-235B-A22B

* State-of-the-art vision-language understanding
* Best for research and high-end applications

### Instruct vs Thinking

**Instruct Editions**:

* Optimized for following user instructions
* Better for general-purpose applications
* More aligned with human preferences

**Thinking Editions**:

* Enhanced reasoning capabilities
* Better for complex problem-solving
* Excels in STEM and mathematical tasks

## Related Resources

* [Installation Guide](https://mintlify.com/QwenLM/Qwen3-VL/installation.md)
* [Quickstart](https://mintlify.com/QwenLM/Qwen3-VL/quickstart.md)
* [Deployment](https://mintlify.com/QwenLM/Qwen3-VL/deployment/vllm.md)
* [Benchmarks](https://mintlify.com/QwenLM/Qwen3-VL/resources/benchmarks.md)


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.