WAS Node Suite (Revised)

By Dr.Lt.DataView on GitHub →

A massive node pack consisting of over 200 nodes, including image processing, masking, text handling, and arithmetic operations. NOTE: A replacement node pack provided for existing users following the retirement of the original author of the widely used WAS Node Suite.

How much VRAM does WAS Node Suite (Revised) require?

Direct Answer: The ComfyUI node WAS Node Suite (Revised) requires a minimum base VRAM of 2048MB and is optimized for GPUs with at least 6GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.

High (2-4GB)
Base VRAM:
2048MB (2.0GB)
Recommended GPU:
6GB+ 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!

Deploy on High-Performance GPUs

Need more VRAM to run ComfyUI with this node? Rent low-cost, high-performance GPUs on Vast.ai instantly.

🚀 Deploy on Vast.ai

Deploy on Cloud GPUs

Need more VRAM to run ComfyUI with this node? Rent low-cost, high-performance cloud GPUs on RunPod instantly.

🚀 Deploy on RunPod

What Python packages are required for WAS Node Suite (Revised)?

Direct Answer: Running WAS Node Suite (Revised) requires installing the following Python package dependencies: cmake, fairscale>=0.4.4, gitpython, imageio, joblib, matplotlib, numba>=0.62, numpy, opencv-python-headless, pilgram, rembg, scikit-image>=0.20.0, scikit-learn, scipy, timm>=0.4.12, tqdm, transformers. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
cmake
fairscale>=0.4.4
gitpython
imageio
joblib
matplotlib
numba>=0.62
numpy
opencv-python-headless
pilgram
rembg
scikit-image>=0.20.0
scikit-learn
scipy
timm>=0.4.12
tqdm
transformers

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

Frequently Asked Questions

How much VRAM does WAS Node Suite (Revised) require?

WAS Node Suite (Revised) requires a minimum of 2048MB (2.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 6GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.

Can I run WAS Node Suite (Revised) on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 8.8GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 8.8GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 12.4GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 19.6GB headroom

What Python packages are required for WAS Node Suite (Revised)?

To run WAS Node Suite (Revised), you need to install: cmake, fairscale>=0.4.4, gitpython, imageio, joblib, matplotlib, numba>=0.62, numpy, opencv-python-headless, pilgram, rembg, scikit-image>=0.20.0, scikit-learn, scipy, timm>=0.4.12, tqdm, transformers. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running WAS Node Suite (Revised)?

WAS Node Suite (Revised) 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 WAS Node Suite (Revised) in ComfyUI?

To install WAS Node Suite (Revised): (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/ltdrdata/was-node-suite-comfyui, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.