HyperAI

1. Tutorial Introduction

Qwen-Image is a large model for high-quality image generation and editing released by Alibaba Tongyi Qianwen team in August 2025. This model has achieved a breakthrough in the field of text rendering, supports high-fidelity output of multi-line paragraphs in both Chinese and English, and has the ability to accurately restore complex scenes and millimeter-level details. Qwen-Image uses a multi-task collaborative training paradigm to achieve pixel-level consistency in image editing, ensuring zero drift of the subject, light and shadow, and texture throughout the process. It can generate dozens of styles such as realism, animation, cyberpunk, science fiction, minimalism, retro, surrealism, ink painting, etc. with one click, and supports full-dimensional fine operations such as style transfer, element addition and deletion, detail enhancement, text redrawing, and posture reset. The relevant paper results are "Qwen-Image Technical Report".

This tutorial uses dual-card RTX A6000 resources.

2. Project Examples

3. Operation steps

1. After starting the container, click the API address to enter the Web interface

2. Usage steps

If "Bad Gateway" is displayed, it means the model is initializing. Since the model is large, please wait about 2-3 minutes and refresh the page.

Parameter Description

Advanced Settings:
- Negative prompt: Negative prompt words are used to specify content or styles that are not desired to appear in the image.
- Seed: Random seed.
- Randomize seed: Whether to automatically randomize the seed.
- Image size (ratio): Controls the resolution ratio of the output image.
- Guidance scale: Guidance scale, used to control the quality of the generated image.
- Number of inference steps: The number of inference steps used to control the level of detail of the generated image.

4. Discussion

🖌️ If you see a high-quality project, please leave a message in the background to recommend it! In addition, we have also established a tutorial exchange group. Welcome friends to scan the QR code and remark [SD Tutorial] to join the group to discuss various technical issues and share application effects↓

Citation Information

The citation information for this project is as follows:

@article{qwen-image,
    title={Qwen-Image Technical Report}, 
    author={Qwen Team},
    journal={arXiv preprint},
    year={2025}
}