ComfyUI_Lam

By Lam YanView on GitHub →

This extension has some useful nodes, loops, wechat public number +AI chat drawing, distributed cluster

How much VRAM does ComfyUI_Lam require?

Direct Answer: The ComfyUI node ComfyUI_Lam 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.

High (2-4GB)
Base VRAM:
128MB (0.1GB)
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!

Deploy on High-Performance GPUs

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🚀 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.

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What Python packages are required for ComfyUI_Lam?

Direct Answer: Running ComfyUI_Lam requires installing the following Python package dependencies: asyncio, av==10.0.0, basicsr==1.4.2, customtkinter==5.2.0, dlib-bin, edge_tts, face_alignment==1.3.5, facexlib==0.3.0, ffmpy==0.3.0, gfpgan==1.3.8, gitpython, gradio==3.23.0, imageio==2.19.3, imageio-ffmpeg==0.4.7, insightface==0.7.3, joblib==1.1.0, kornia==0.6.8, librosa==0.9.2, numba==0.56.4, numpy==1.23.4, omegaconf==2.3.0, onnxruntime==1.15.1, openai, opencv-python==4.7.0.72, pillow==9.4.0, pydub==0.25.1, pytorch-lightning==1.7.7, pyyaml==6.0, pyzbar, qrcode==7.4.2, resampy==0.3.1, safetensors==0.3.1, scikit-image==0.19.3, scipy==1.10.1, tensorflow==2.12.0 -i https://pypi.tuna.tsinghua.edu.cn/simple, tkinterdnd2==0.3.0, torchmetrics==0.11.4, tqdm==4.64.1, yacs==0.1.8. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
asyncio
av==10.0.0
basicsr==1.4.2
customtkinter==5.2.0
dlib-bin
edge_tts
face_alignment==1.3.5
facexlib==0.3.0
ffmpy==0.3.0
gfpgan==1.3.8
gitpython
gradio==3.23.0
imageio==2.19.3
imageio-ffmpeg==0.4.7
insightface==0.7.3
joblib==1.1.0
kornia==0.6.8
librosa==0.9.2
numba==0.56.4
numpy==1.23.4
omegaconf==2.3.0
onnxruntime==1.15.1
openai
opencv-python==4.7.0.72
pillow==9.4.0
pydub==0.25.1
pytorch-lightning==1.7.7
pyyaml==6.0
pyzbar
qrcode==7.4.2
resampy==0.3.1
safetensors==0.3.1
scikit-image==0.19.3
scipy==1.10.1
tensorflow==2.12.0  -i https://pypi.tuna.tsinghua.edu.cn/simple
tkinterdnd2==0.3.0
torchmetrics==0.11.4
tqdm==4.64.1
yacs==0.1.8

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:

ATI_AudioReactive
by yukascomfy1.5GB VRAM
Akatz Custom Nodes
by akatz-ai128MB VRAM
Artha-Gemini
by Cyrostar4.0GB VRAM
Bjornulf_custom_nodes
by justUmen256MB VRAM

Frequently Asked Questions

How much VRAM does ComfyUI_Lam require?

ComfyUI_Lam 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_Lam 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_Lam need?

ComfyUI_Lam requires the following PyTorch-related packages: pytorch-lightning==1.7.7, torchmetrics==0.11.4. 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_Lam?

To run ComfyUI_Lam, you need to install: asyncio, av==10.0.0, basicsr==1.4.2, customtkinter==5.2.0, dlib-bin, edge_tts, face_alignment==1.3.5, facexlib==0.3.0, ffmpy==0.3.0, gfpgan==1.3.8, gitpython, gradio==3.23.0, imageio==2.19.3, imageio-ffmpeg==0.4.7, insightface==0.7.3, joblib==1.1.0, kornia==0.6.8, librosa==0.9.2, numba==0.56.4, numpy==1.23.4, omegaconf==2.3.0, onnxruntime==1.15.1, openai, opencv-python==4.7.0.72, pillow==9.4.0, pydub==0.25.1, pytorch-lightning==1.7.7, pyyaml==6.0, pyzbar, qrcode==7.4.2, resampy==0.3.1, safetensors==0.3.1, scikit-image==0.19.3, scipy==1.10.1, tensorflow==2.12.0 -i https://pypi.tuna.tsinghua.edu.cn/simple, tkinterdnd2==0.3.0, torchmetrics==0.11.4, tqdm==4.64.1, yacs==0.1.8. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ComfyUI_Lam?

ComfyUI_Lam 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_Lam in ComfyUI?

To install ComfyUI_Lam: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/yanlang0123/ComfyUI_Lam, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.