ComfyUI WD 1.4 Tagger

By pythongosssssView on GitHub →

A ComfyUI extension allowing the interrogation of booru tags from images.

How much VRAM does ComfyUI WD 1.4 Tagger require?

Direct Answer: The ComfyUI node ComfyUI WD 1.4 Tagger requires a minimum base VRAM of 512MB 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:
512MB (0.5GB)
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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What Python packages are required for ComfyUI WD 1.4 Tagger?

Direct Answer: Running ComfyUI WD 1.4 Tagger requires installing the following Python package dependencies: onnxruntime. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
onnxruntime

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-Regex-Runner
by orange90256MB VRAM
AIGODLIKE-COMFYUI-TRANSLATION
by AIGODLIKE128MB VRAM
AIRedoon
by purpen256MB VRAM
AITocha Vision
by aitocha128MB VRAM

Frequently Asked Questions

How much VRAM does ComfyUI WD 1.4 Tagger require?

ComfyUI WD 1.4 Tagger requires a minimum of 512MB (0.5GB) 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 WD 1.4 Tagger on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 10.3GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.3GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 13.9GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.1GB headroom

What Python packages are required for ComfyUI WD 1.4 Tagger?

To run ComfyUI WD 1.4 Tagger, you need to install: onnxruntime. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ComfyUI WD 1.4 Tagger?

ComfyUI WD 1.4 Tagger 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 WD 1.4 Tagger in ComfyUI?

To install ComfyUI WD 1.4 Tagger: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/pythongosssss/ComfyUI-WD14-Tagger, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.