comfyui-memory-manager

By darshd9941View on GitHub →

ComfyUI custom nodes for preventing OOM crashes with real-time VRAM monitoring, automatic model unloading, LRU cache, and memory budget gates.

How much VRAM does comfyui-memory-manager require?

Direct Answer: The ComfyUI node comfyui-memory-manager requires a minimum base VRAM of 256MB 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:
256MB (0.3GB)
Recommended GPU:
4GB+ VRAM
Low VRAM Mode:
✓ Supported
Estimation Confidence:
HIGH

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.

🚀 Deploy on RunPod

What Python packages are required for comfyui-memory-manager?

Direct Answer: Running comfyui-memory-manager requires installing the following Python package dependencies: torch>=2.0. This node specifically requires PyTorch version 2.0 or newer.

requirements.txt
torch>=2.0

Interactive Setup & Dependency Resolver

Operating System:
Environment Type:
Run this terminal command in your ComfyUI root folder:
# Loading command...

Special Environment Requirements:

Requires PyTorch version 2.0+.

To update PyTorch for your selected setup, run:
# Loading PyTorch command...

Related Custom Nodes

The following custom nodes run in the same PyTorch / CUDA environment and share similar categories or workflows:

CNP Crop And Paste
by dapa5900128MB VRAM
ComfyUI Temporal Mask Tools
by nomadoor256MB VRAM
ComfyUI-RndNanthu
by RndNanthu128MB VRAM
comfyui-ghostwritten-BiRefNet
by GhostwrittenStudios128MB VRAM
comfyui-unlimited-ocr
by PsychoLogicAu128MB VRAM

Frequently Asked Questions

How much VRAM does comfyui-memory-manager require?

comfyui-memory-manager requires a minimum of 256MB (0.3GB) 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-memory-manager on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 14.2GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.4GB headroom

What PyTorch version does comfyui-memory-manager need?

comfyui-memory-manager requires the following PyTorch-related packages: torch>=2.0. 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-memory-manager?

To run comfyui-memory-manager, you need to install: torch>=2.0. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running comfyui-memory-manager?

comfyui-memory-manager 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-memory-manager in ComfyUI?

To install comfyui-memory-manager: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/darshd9941/comfyui-memory-manager, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.