UNO | Consistent Subject & Object Generation

ComfyUI UNO Description

1. What is ComfyUI UNO?

The ComfyUI UNO workflow integrates ByteDance's Universal aNd cOntrollable (UNO) model into the ComfyUI environment. Developed by ByteDance's Intelligent Creation Team, UNO represents a significant advancement in subject-driven image generation technology based on the innovative "Less-to-More" generalization paradigm. ComfyUI UNO workflow enables flexible and high-fidelity image generation while preserving identity features of reference subjects with remarkable consistency across various contexts and scenarios.

2. Benefits of ComfyUI UNO:

• Superior Subject Consistency: ComfyUI UNO maintains exceptional subject similarity across different context.
• Subject-Object Control: Unlike many alternatives, ComfyUI UNO excels at handling both subject references and object references simultaneously without identity confusion.
• Universal Compatibility: ComfyUI UNO works with diverse types of subjects - people, objects, toys, logos, and more.
• Resource Efficiency: ComfyUI UNO delivers professional-quality results even with limited VRAM resources (works well with 24GB).
• Flexible Implementation: ComfyUI UNO includes workflows for both single-subject and subject-object generation.

3. How to Use ComfyUI UNO

3.1 Workflow Setup

ComfyUI UNO workflow has two main configurations:

Top Group - Subject-Object Generation:

• This configuration allows you to input a reference subject image and a reference object image that will be combined in a generated scene according to your text prompt.

Bottom Group - Single-Subject Generation:

• This configuration uses a single reference image and generates new images of that subject in different contexts.

3.2 Generation Process with ComfyUI UNO

Basic Setup:

1. Load Reference Images:
   • For subject-object workflow (top group): Upload one subject reference image and one object reference image
   • For single-subject workflow (bottom group): Upload one reference image
2. Set Text Prompt for ComfyUI UNO:
   • Write a descriptive prompt for your desired scene, including how the reference subject/object should appear
3. Adjust ComfyUI UNO Parameters:
   • Width/Height: Determine output resolution (recommended 768×1024 or 1024×1024)
   • Guidance: Controls how closely ComfyUI UNO generation follows your text prompt (3.5-4.0 recommended)
   • Num_steps: Higher values (20+) produce more consistent results with ComfyUI UNO, especially for human faces
   • Seed: Set a specific seed for reproducibility or randomize for variety in ComfyUI UNO outputs
4. Generate Image with ComfyUI UNO:
   • Click "Queue Prompt" to run the ComfyUI UNO workflow
   • Review the result in the "Save Image" node

3.3 Parameter Reference for ComfyUI UNO

UNO Loadmodel Node:

• model_type: Determines which ComfyUI UNO model variant to use
  • flux-dev: Standard ComfyUI UNO model with good balance of quality and performance
  • flux-schnell: Faster ComfyUI UNO model variant with slightly lower quality

3.4 Tips for Best Results with ComfyUI UNO

Subject Selection for ComfyUI UNO:

• Choose clear, well-lit reference images where the subject is prominent
• For faces/people, front-facing images with neutral expressions work best with ComfyUI UNO
• For objects, clear images with minimal background distraction are ideal for ComfyUI UNO processing

Prompt Engineering for ComfyUI UNO:

• Be specific about subject descriptions that match your reference images
• Describe the desired scene, lighting, and composition for ComfyUI UNO to generate
• Include reference to the specific subjects (e.g., "a young man", "a vintage bicycle")
• Keep prompts concise but detailed for optimal ComfyUI UNO results

4. Technical Information about ComfyUI UNO

The ComfyUI UNO technology is built upon FLUX models and leverages the DiT (Diffusion Transformer) architecture with several key enhancements:

• Universal Rotary Position Embedding (UnoPE): A specialized mechanism in ComfyUI UNO that helps the model differentiate between reference subjects and objects, significantly reducing attribute confusion.
• Progressive Cross-Modal Alignment: Training methodology that enables ComfyUI UNO to handle increasingly complex multi-condition controls.
• Universal Customization: ComfyUI UNO is capable of handling diverse subject types without specialized training.

5. Acknowledgements

This ComfyUI workflow is powered by UNO, developed by the Intelligent Creation Team at ByteDance (Shaojin Wu, Mengqi Huang, Wenxu Wu, Yufeng Cheng, Fei Ding, and Qian He). The ComfyUI integration of ByteDance's UNO is provided by community contributors, adapting the groundbreaking research into an accessible workflow.

For additional information about UNO, visit the .