ae-in-workflow

By by-aeView on GitHub →

In-workflow Nodes for ComfyUI - Heavy interaction and streaming capabilities

How much VRAM does ae-in-workflow require?

Direct Answer: The ComfyUI node ae-in-workflow 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

Need more VRAM to run ComfyUI with this node? Rent low-cost, high-performance GPUs on Vast.ai instantly.

🚀 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 ae-in-workflow?

Direct Answer: Running ae-in-workflow requires installing the following Python package dependencies: numpy>=1.19.0, pillow>=8.0.0, pygame>=2.0.0, safetensors>=0.4.0, screeninfo>=0.8.0, torch>=1.9.0. This node specifically requires PyTorch version 1.9.0 or newer.

requirements.txt
numpy>=1.19.0
pillow>=8.0.0
pygame>=2.0.0
safetensors>=0.4.0
screeninfo>=0.8.0
torch>=1.9.0

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 1.9.0+.

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:

ComfyUI API Image Edit
by aiaiaikkk128MB VRAM
ComfyUI ASDF Pixel Sort Nodes
by A043-studios128MB VRAM
ComfyUI HTTP - REST API Nodes
by wawahuy128MB VRAM
ComfyUI LoRA Combine Node
by LukeCoulson1128MB VRAM
ComfyUI Load Image From URL
by papcorns128MB VRAM

Frequently Asked Questions

How much VRAM does ae-in-workflow require?

ae-in-workflow 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 ae-in-workflow 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 ae-in-workflow need?

ae-in-workflow requires the following PyTorch-related packages: torch>=1.9.0. 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 ae-in-workflow?

To run ae-in-workflow, you need to install: numpy>=1.19.0, pillow>=8.0.0, pygame>=2.0.0, safetensors>=0.4.0, screeninfo>=0.8.0, torch>=1.9.0. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ae-in-workflow?

ae-in-workflow 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 ae-in-workflow in ComfyUI?

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