Installation and Features

中文

🎉 MAJOR UPDATE: v1.60 - Simplified Installation (No Integration Required!)

As of v1.60, manual integration with ComfyUI-nunchaku's __init__.py is completely unnecessary.

The node now operates as a fully independent custom node that works out-of-the-box. Simply clone the repository into your custom_nodes folder and restart ComfyUI. The nodes will automatically appear in ComfyUI's node menu through ComfyUI's built-in automatic node loading mechanism.

What Changed in v1.60

✅ Removed dependency on ComfyUI-nunchaku integration - The LoRA loader is now a standalone plugin
✅ Simplified installation - No batch scripts or manual file editing required
✅ Cleaner architecture - Node registration happens automatically
✅ Backward compatible - All existing LoRA files and workflows continue to work

For a detailed technical explanation of why integration is no longer needed, see v1.60 Release Notes

Features

NunchakuQwenImageLoraLoader: Load and apply single LoRA to Qwen Image models
NunchakuQwenImageLoraStack: Apply multiple LoRAs with dynamic UI control
NunchakuQwenImageDiffsynthControlnet: Apply diffsynth ControlNet to Nunchaku Qwen Image models (v2.0)
Dynamic VRAM Management: Automatic CPU offloading based on available VRAM
LoRA Composition: Efficient LoRA stacking and composition
ComfyUI Integration: Seamless integration with ComfyUI workflows

Installation

Quick Installation (v1.60 - Simplified!)

Prerequisites:

ComfyUI-nunchaku must be installed

Clone this repository to your ComfyUI custom_nodes directory:

cd ComfyUI/custom_nodes
git clone https://github.com/ussoewwin/ComfyUI-QwenImageLoraLoader.git

Restart ComfyUI

That's it! The nodes will automatically appear in ComfyUI's node menu.

Manual Installation (Alternative)

If you prefer to install manually or are using macOS/Linux:

cd /path/to/ComfyUI/custom_nodes
git clone https://github.com/ussoewwin/ComfyUI-QwenImageLoraLoader.git

Then restart ComfyUI.

Requirements

Python 3.12+
ComfyUI (latest version recommended)
ComfyUI-nunchaku (required)
CUDA-capable GPU (optional, but recommended for performance)

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