comfyui-nvidia-audio-diffusion
A ComfyUI custom node suite for Audio-to-Audio Schrödinger Bridges (A2SB) with state-of-the-art audio restoration, bandwidth extension, and inpainting optimized for modern NVIDIA GPUs.
How much VRAM does comfyui-nvidia-audio-diffusion require?
Direct Answer: The ComfyUI node comfyui-nvidia-audio-diffusion requires a minimum base VRAM of 1536MB and is optimized for GPUs with at least 6GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.
- Base VRAM:
- 1536MB (1.5GB)
- Recommended GPU:
- 6GB+ 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!
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Deploy on Cloud GPUs
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What Python packages are required for comfyui-nvidia-audio-diffusion?
Direct Answer: Running comfyui-nvidia-audio-diffusion requires installing the following Python package dependencies: einops>=0.6.1, librosa>=0.10.0, rotary-embedding-torch>=0.3.5, soundfile>=0.12.1, torchao. Ensure your ComfyUI environment has these packages active before launching.
einops>=0.6.1
librosa>=0.10.0
rotary-embedding-torch>=0.3.5
soundfile>=0.12.1
torchaoInteractive Setup & Dependency Resolver
# Loading command...Frequently Asked Questions
How much VRAM does comfyui-nvidia-audio-diffusion require?
comfyui-nvidia-audio-diffusion requires a minimum of 1536MB (1.5GB) 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 comfyui-nvidia-audio-diffusion on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 9.3GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 9.3GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 12.9GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 20.1GB headroom
What PyTorch version does comfyui-nvidia-audio-diffusion need?
comfyui-nvidia-audio-diffusion requires the following PyTorch-related packages: rotary-embedding-torch>=0.3.5, torchao. 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 comfyui-nvidia-audio-diffusion?
To run comfyui-nvidia-audio-diffusion, you need to install: einops>=0.6.1, librosa>=0.10.0, rotary-embedding-torch>=0.3.5, soundfile>=0.12.1, torchao. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running comfyui-nvidia-audio-diffusion?
comfyui-nvidia-audio-diffusion 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-nvidia-audio-diffusion in ComfyUI?
To install comfyui-nvidia-audio-diffusion: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/mmoalem/comfyui-nvidia-audio-diffusion, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.