LLM Node for ComfyUI
The LLM_Node enhances ComfyUI by integrating advanced language model capabilities, enabling a wide range of NLP tasks such as text generation, content summarization, question answering, and more. This flexibility is powered by various transformer model architectures from the transformers library, allowing for the deployment of models like T5, GPT-2, and others based on your project's needs.
Quick Technical Summary: LLM Node for ComfyUI
- Base VRAM Footprint:
- 256 MB (4 GB Tier)
- Primary Dependencies:
- accelerate, llama-cpp-python, torch>=1.7.1, transformers>=4.0.0
- Min PyTorch / CUDA:
- PyTorch 1.7.1 | CUDA 12.1+
- GitHub Repository:
- https://github.com/Big-Idea-Technology/ComfyUI_LLM_Node
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does LLM Node for ComfyUI require?
Direct Answer: The ComfyUI node LLM Node for ComfyUI 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.
- Base VRAM:
- 256MB (0.3GB)
- Recommended GPU:
- 4GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- HIGH
Cheapest VRAM Upgrade Paths (Live Market Prices):
- GeForce RTX 3060 12GB (Ultimate Budget VRAM King)──► Used: $209.62View eBay ↗
- GeForce RTX 4060 8GB (Modern Entry-Level)──► New: $303.50View Amazon ↗
Interactive VRAM Compatibility Estimator
Your GPU has plenty of headroom. You can run this node safely with your active configurations!
Verify Compatibility for Your Specific GPU VRAM
Select your graphics card's VRAM capacity to view optimized batch sizes, suggested resolutions, and custom performance tips for LLM Node for ComfyUI:
Buy NVIDIA GeForce RTX 3060 (12GB VRAM)
Tired of renting cloud rigs? Run ComfyUI locally with absolute zero latency. Best entry-level ComfyUI experience. Avoids immediate VRAM limitations on basic LoRA training.
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What Python packages are required for LLM Node for ComfyUI?
Direct Answer: Running LLM Node for ComfyUI requires installing the following Python package dependencies: accelerate, llama-cpp-python, torch>=1.7.1, transformers>=4.0.0. This node specifically requires PyTorch version 1.7.1 or newer.
accelerate
llama-cpp-python
torch>=1.7.1
transformers>=4.0.0Interactive Setup & Dependency Resolver
# Loading command...Special Environment Requirements:
Requires PyTorch version 1.7.1+.
# Loading PyTorch command...Frequently Asked Questions
How much VRAM does LLM Node for ComfyUI require?
LLM Node for ComfyUI 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 LLM Node for ComfyUI 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
How much VRAM does LLM Node for ComfyUI take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), LLM Node for ComfyUI runs smoothly on an RTX 3060 (12GB) with 10.6GB of headroom. This is sufficient to run the node alongside standard SD 1.5 and SDXL workflows in full precision. On an RTX 4090 (24GB VRAM), the node runs with extreme headroom on an RTX 4090 (24GB) with 21.4GB of dedicated headroom. This allows you to combine the node with massive models (like FLUX.1 Dev, Schnell, or Hunyuan Video) in full precision (FP16) without any offload flags.
What PyTorch version does LLM Node for ComfyUI need?
LLM Node for ComfyUI requires the following PyTorch-related packages: torch>=1.7.1. 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 LLM Node for ComfyUI?
To run LLM Node for ComfyUI, you need to install: accelerate, llama-cpp-python, torch>=1.7.1, transformers>=4.0.0. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running LLM Node for ComfyUI?
LLM Node for ComfyUI 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 LLM Node for ComfyUI in ComfyUI?
To install LLM Node for ComfyUI: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/Big-Idea-Technology/ComfyUI_LLM_Node, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.