JoyHallo-ComfyUI
a custom node for [a/JoyHallo](https://github.com/jdh-algo/JoyHallo)
How much VRAM does JoyHallo-ComfyUI require?
Direct Answer: The ComfyUI node JoyHallo-ComfyUI 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.
- Base VRAM:
- 128MB (0.1GB)
- Recommended GPU:
- 4GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- MEDIUM
Interactive VRAM Compatibility Estimator
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 Cloud GPUs
Need more VRAM to run ComfyUI with this node? Rent low-cost, high-performance cloud GPUs on RunPod instantly.
What Python packages are required for JoyHallo-ComfyUI?
Direct Answer: Running JoyHallo-ComfyUI requires installing the following Python package dependencies: accelerate, audio-separator, av, bitsandbytes, decord, diffusers, einops, insightface, isort, librosa, mediapipe==0.10.14, mlflow, moviepy, numpy, omegaconf, onnx, onnx2torch, onnxruntime-gpu, opencv-contrib-python, opencv-python, opencv-python-headless, pillow, pre-commit, pylint, tqdm, transformers. Ensure your ComfyUI environment has these packages active before launching.
accelerate
audio-separator
av
bitsandbytes
decord
diffusers
einops
insightface
isort
librosa
mediapipe==0.10.14
mlflow
moviepy
numpy
omegaconf
onnx
onnx2torch
onnxruntime-gpu
opencv-contrib-python
opencv-python
opencv-python-headless
pillow
pre-commit
pylint
tqdm
transformersInteractive Setup & Dependency Resolver
# Loading command...Frequently Asked Questions
How much VRAM does JoyHallo-ComfyUI require?
JoyHallo-ComfyUI 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 JoyHallo-ComfyUI 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 PyTorch version does JoyHallo-ComfyUI need?
JoyHallo-ComfyUI requires the following PyTorch-related packages: onnx2torch. Ensure your ComfyUI environment has these installed. Ensure your PyTorch installation matches your CUDA version (use torch.version.cuda to check).
What Python packages are required for JoyHallo-ComfyUI?
To run JoyHallo-ComfyUI, you need to install: accelerate, audio-separator, av, bitsandbytes, decord, diffusers, einops, insightface, isort, librosa, mediapipe==0.10.14, mlflow, moviepy, numpy, omegaconf, onnx, onnx2torch, onnxruntime-gpu, opencv-contrib-python, opencv-python, opencv-python-headless, pillow, pre-commit, pylint, tqdm, transformers. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running JoyHallo-ComfyUI?
JoyHallo-ComfyUI 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 JoyHallo-ComfyUI in ComfyUI?
To install JoyHallo-ComfyUI: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/AIFSH/JoyHallo-ComfyUI, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.