ComfyUI-TransformerLLMTaskRunner

By mkim87404View on GitHub →

A dependency-safe and memory-conscious ComfyUI custom node that runs basic Transformer LLMs directly inside ComfyUI workflows.

How much VRAM does ComfyUI-TransformerLLMTaskRunner require?

Direct Answer: The ComfyUI node ComfyUI-TransformerLLMTaskRunner 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.

🚀 Deploy on RunPod

What Python packages are required for ComfyUI-TransformerLLMTaskRunner?

Direct Answer: Running ComfyUI-TransformerLLMTaskRunner requires installing the following Python package dependencies: accelerate# works with whatever torch, CUDA, or transformers you already have installed, no pinning, huggingface_hub# harmless library for interfacing Hugging Face. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
accelerate# works with whatever torch, CUDA, or transformers you already have installed, no pinning
huggingface_hub# harmless library for interfacing Hugging Face

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:

AITocha Vision
by aitocha128MB VRAM
AI_Text_Comfyui
by Zch6111256MB VRAM
AK XZ Axis (XY for any KSampler)
by akawana256MB VRAM
ArtyClaw Comfy Nodes
by artyclaw256MB VRAM

Frequently Asked Questions

How much VRAM does ComfyUI-TransformerLLMTaskRunner require?

ComfyUI-TransformerLLMTaskRunner 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-TransformerLLMTaskRunner 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-TransformerLLMTaskRunner need?

ComfyUI-TransformerLLMTaskRunner requires the following PyTorch-related packages: accelerate# works with whatever torch, CUDA, or transformers you already have installed, no pinning. 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-TransformerLLMTaskRunner?

To run ComfyUI-TransformerLLMTaskRunner, you need to install: accelerate# works with whatever torch, CUDA, or transformers you already have installed, no pinning, huggingface_hub# harmless library for interfacing Hugging Face. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ComfyUI-TransformerLLMTaskRunner?

ComfyUI-TransformerLLMTaskRunner 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-TransformerLLMTaskRunner in ComfyUI?

To install ComfyUI-TransformerLLMTaskRunner: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/mkim87404/ComfyUI-TransformerLLMTaskRunner, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.