1. Tutorial Introduction

HunyuanImage-2.1 is an open source literary image model launched by the Tencent Hunyuan team in September 2025. It supports native 2K resolution, has powerful complex semantic understanding capabilities, and can accurately generate scene details, character expressions and actions. The model supports Chinese and English input and can generate images in various styles, such as comics, figurines, etc., while maintaining stable control over the text and details in the image. The model is based on technologies such as dual-channel text encoder and high-compression VAE, which greatly improves training and inference efficiency. The relevant paper results are "PromptEnhancer: A Simple Approach to Enhance Text-to-Image Models via Chain-of-Thought Prompt Rewriting".

This tutorial uses a single RTX PRO 6000 graphics card as computing resource, providing two functions: Text-to-Image Generation and Image Refinement for testing.

2. Effect display

Text-to-image Generation

Image Refinement

3. Operation steps

1. Start the container

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.

2. Usage steps

1. Text-to-image Generation

Parameter Description:

• Use Distilled Model: Using distilled model will generate faster results but slightly lower quality.
• Prompt: You can enter text here.
• Negative Prompt: A negative prompt that tells the AI "not to generate something".
• Aspect Ratio: Select the aspect ratio of the generated image.
• Inference Steps: Inference steps. More steps = better quality, slower generation speed.
• Guidance Scale: How strictly prompts are followed.
• Seed: seed.
• Use Refiner: Whether to use image refinement.

2. Image Refinement

Parameter Description:

• Refinement Prompt: You can enter text here.
• Width: Output image width.
• Height: Output image height.
• Refinement Steps: Refine the reasoning steps. More steps = better quality, slower generation speed.
• Guidance Scale: How strictly prompts are followed.
• Seed: seed.

4. Discussion

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Citation Information

The citation information for this project is as follows:

@misc{HunyuanImage-2.1,
  title={HunyuanImage 2.1: An Efficient Diffusion Model for High-Resolution (2K) Text-to-Image Generation},
  author={Tencent Hunyuan Team},
  year={2025},
  howpublished={\url{https://github.com/Tencent-Hunyuan/HunyuanImage-2.1}},
}