ComfyUI_RH_QwenImageI2L

By HM-RunningHubView on GitHub →

A ComfyUI custom node that generates Image-to-LoRA (I2L) LoRA from training images using DiffSynth-Studio Qwen-Image i2L pipelines.

How much VRAM does ComfyUI_RH_QwenImageI2L require?

Direct Answer: The ComfyUI node ComfyUI_RH_QwenImageI2L requires a minimum base VRAM of 128MB and is optimized for GPUs with at least 4GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.

High (2-4GB)
Base VRAM:
128MB (0.1GB)
Recommended GPU:
4GB+ VRAM
Low VRAM Mode:
✓ Supported
Estimation Confidence:
MEDIUM

Interactive VRAM Compatibility Estimator

Estimated Total VRAM: 3.00 GBTarget: 8 GB
✅ Comfortable Fit

Your GPU has plenty of headroom. You can run this node safely with your active configurations!

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Deploy on Cloud GPUs

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What Python packages are required for ComfyUI_RH_QwenImageI2L?

Direct Answer: Running ComfyUI_RH_QwenImageI2L requires installing the following Python package dependencies: modelscope, numpy, pillow, safetensors. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
modelscope
numpy
pillow
safetensors

Interactive Setup & Dependency Resolver

Operating System:
Environment Type:
Run this terminal command in your ComfyUI root folder:
# Loading command...

Related Custom Nodes

The following custom nodes run in the same PyTorch / CUDA environment and share similar categories or workflows:

ComfyUI_RH_ZImageI2L
by HM-RunningHub128MB VRAM
Anima Edit LoRA
by wochenlong128MB VRAM
Comfy Nano Banana
by darkamenosa256MB VRAM
ComfyUI HiTem3D Integration
by GeekatplayStudio256MB VRAM
ComfyUI Image Picker
by TechnoWarrior2128MB VRAM

Frequently Asked Questions

How much VRAM does ComfyUI_RH_QwenImageI2L require?

ComfyUI_RH_QwenImageI2L requires a minimum of 128MB (0.1GB) of VRAM for base operation. For optimal performance, a GPU with at least 4GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.

Can I run ComfyUI_RH_QwenImageI2L on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 10.7GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.7GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 14.3GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.5GB headroom

What Python packages are required for ComfyUI_RH_QwenImageI2L?

To run ComfyUI_RH_QwenImageI2L, you need to install: modelscope, numpy, pillow, safetensors. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ComfyUI_RH_QwenImageI2L?

ComfyUI_RH_QwenImageI2L supports low VRAM mode. To reduce memory usage: (1) Enable --lowvram or --medvram flags in ComfyUI, (2) Reduce batch size to 1, (3) Use fp16 or fp8 precision if supported, (4) Close other GPU applications.

How do I install ComfyUI_RH_QwenImageI2L in ComfyUI?

To install ComfyUI_RH_QwenImageI2L: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/HM-RunningHub/ComfyUI_RH_QwenImageI2L, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.