ComfyUI-Lumina-DiMOO
ComfyUI wrapper nodes for Lumina-DiMOO. Please see the README for model weight download instructions.
How much VRAM does ComfyUI-Lumina-DiMOO require?
Direct Answer: The ComfyUI node ComfyUI-Lumina-DiMOO 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!
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Deploy on Cloud GPUs
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What Python packages are required for ComfyUI-Lumina-DiMOO?
Direct Answer: Running ComfyUI-Lumina-DiMOO requires installing the following Python package dependencies: accelerate, bitsandbytes, diffusers==0.34.0, einops, fairscale, gradio==4.19.0, h5py, httpx, ninja, packaging, pandas, pathlib, pre-commit, pytorch_lightning, pyyaml, regex, sentencepiece, tensorboard, torch==2.3.1, torchao==0.11.0, torchaudio==2.3.1, torchvision==0.18.1, transformers==4.46.2. Ensure your ComfyUI environment has these packages active before launching.
accelerate
bitsandbytes
diffusers==0.34.0
einops
fairscale
gradio==4.19.0
h5py
httpx
ninja
packaging
pandas
pathlib
pre-commit
pytorch_lightning
pyyaml
regex
sentencepiece
tensorboard
torch==2.3.1
torchao==0.11.0
torchaudio==2.3.1
torchvision==0.18.1
transformers==4.46.2Interactive Setup & Dependency Resolver
# Loading command...Frequently Asked Questions
How much VRAM does ComfyUI-Lumina-DiMOO require?
ComfyUI-Lumina-DiMOO 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-Lumina-DiMOO 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 ComfyUI-Lumina-DiMOO need?
ComfyUI-Lumina-DiMOO requires the following PyTorch-related packages: pytorch_lightning, torch==2.3.1, torchao==0.11.0, torchaudio==2.3.1, torchvision==0.18.1. 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-Lumina-DiMOO?
To run ComfyUI-Lumina-DiMOO, you need to install: accelerate, bitsandbytes, diffusers==0.34.0, einops, fairscale, gradio==4.19.0, h5py, httpx, ninja, packaging, pandas, pathlib, pre-commit, pytorch_lightning, pyyaml, regex, sentencepiece, tensorboard, torch==2.3.1, torchao==0.11.0, torchaudio==2.3.1, torchvision==0.18.1, transformers==4.46.2. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running ComfyUI-Lumina-DiMOO?
ComfyUI-Lumina-DiMOO 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-Lumina-DiMOO in ComfyUI?
To install ComfyUI-Lumina-DiMOO: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/L-Hugh/ComfyUI-Lumina-DiMOO, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.