ComfyUI > Nodes > ComfyUI-nunchaku

ComfyUI Extension: ComfyUI-nunchaku

Repo Name

ComfyUI-nunchaku

Author
mit-han-lab (Account age: 2545 days)
Nodes
View all nodes(4)
Latest Updated
2025-05-03
Github Stars
0.94K

How to Install ComfyUI-nunchaku

Install this extension via the ComfyUI Manager by searching for ComfyUI-nunchaku
  • 1. Click the Manager button in the main menu
  • 2. Select Custom Nodes Manager button
  • 3. Enter ComfyUI-nunchaku in the search bar
After installation, click the Restart button to restart ComfyUI. Then, manually refresh your browser to clear the cache and access the updated list of nodes.

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ComfyUI-nunchaku Description

ComfyUI-nunchaku is a ComfyUI Node that supports SVDQuant, a post-training quantization method for diffusion models. It quantizes weights and activations to 1-4 bits, reducing memory by 3.5× and latency by 8.7× on a 16GB laptop 4090 GPU.

ComfyUI-nunchaku Introduction

ComfyUI-nunchaku is an extension designed to enhance the capabilities of ComfyUI, a powerful visual AI engine, by integrating the Nunchaku inference engine. This extension is specifically tailored for 4-bit neural networks that have been quantized using the SVDQuant method. By leveraging this technology, ComfyUI-nunchaku allows AI artists to efficiently run complex neural network models with reduced computational resources, making it easier to create high-quality AI-generated art without the need for high-end hardware.

How ComfyUI-nunchaku Works

At its core, ComfyUI-nunchaku utilizes the Nunchaku inference engine, which is optimized for running 4-bit quantized neural networks. The quantization process, known as SVDQuant, involves compressing the model weights and activations to 4 bits, significantly reducing the memory footprint and computational load. This is achieved by absorbing outliers in the data using low-rank components, which helps maintain the model's performance and visual quality. The extension integrates seamlessly with ComfyUI, allowing users to set up and execute workflows that take advantage of these optimizations.

ComfyUI-nunchaku Features

  • Efficient Model Loading: The extension provides nodes for loading various models, including diffusion models and text encoders, optimized for 4-bit quantization.
  • LoRA Support: Users can load and apply multiple LoRA (Low-Rank Adaptation) modules to enhance model performance without re-quantization.
  • ControlNet Integration: ComfyUI-nunchaku supports ControlNet, allowing for more precise control over the generated outputs.
  • First-Block Cache: This feature dynamically caches the output of the first transformer block, reducing computation time for subsequent blocks and speeding up the inference process.
  • FP16 Attention: An optimized attention mechanism that improves performance on supported GPUs without sacrificing precision.

ComfyUI-nunchaku Models

ComfyUI-nunchaku supports a variety of models, each tailored for specific tasks:

  • Flux DiT Models: These are diffusion models optimized for image generation tasks.
  • Text Encoders: Models like T5 and CLIP are used for processing text inputs, essential for text-to-image generation workflows.
  • LoRA Modules: These are used to fine-tune models for specific styles or tasks, providing flexibility in artistic expression.

What's New with ComfyUI-nunchaku

The latest release, v0.2.0, introduces several enhancements:

  • Multi-LoRA Support: Users can now apply multiple LoRA modules simultaneously, offering greater flexibility in model customization.
  • ControlNet Support: Enhanced control over the generated outputs, allowing for more precise artistic direction.
  • 20-Series GPU Compatibility: Expanded support for older GPU models, ensuring broader accessibility.
  • Performance Improvements: The introduction of FP16 attention and First-Block Cache significantly boosts performance, especially on compatible hardware.

Troubleshooting ComfyUI-nunchaku

If you encounter issues while using ComfyUI-nunchaku, consider the following solutions:

  • Model Loading Errors: Ensure that all required models are downloaded and placed in the correct directories. Refer to the installation guide for specific paths.
  • Performance Issues: Adjust the cache_threshold and residual_diff_threshold settings to balance speed and quality. Higher values may improve speed but could affect output quality.
  • Compatibility Problems: Verify that your GPU supports the required features, such as FP16 or specific quantization methods. For Turing GPUs, ensure that nunchaku-fp16 is used instead of unsupported methods.

Learn More about ComfyUI-nunchaku

To further explore the capabilities of ComfyUI-nunchaku, consider visiting the following resources:

  • ComfyUI Examples: Discover various workflows and use cases.
  • Nunchaku GitHub Repository: Access the source code and detailed documentation.
  • Community Forums: Join discussions with other AI artists and developers to share insights and seek assistance. By integrating ComfyUI-nunchaku into your creative process, you can unlock new possibilities in AI-generated art, leveraging advanced quantization techniques to produce stunning results with efficiency and ease.

ComfyUI-nunchaku Related Nodes

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