Pillar_For_ComfyUI
Pillar is an extension plugin for ComfyUI, providing the ability to call local distributed services for ComfyUI. Currently, it integrates the llama-joycaption-beta-one-hf-llava model and offers a distributed deployment solution to solve the problem that the model occupies too many resources and affects the image generation efficiency.
Quick Technical Summary: Pillar_For_ComfyUI
- Base VRAM Footprint:
- 128 MB (4 GB Tier)
- Primary Dependencies:
- fastapi, huggingface_hub, langdetect, pillow, pydantic, requests, torch, torchvision, transformers
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/aicoder-max/Pillar_For_ComfyUI
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does Pillar_For_ComfyUI require?
Direct Answer: The ComfyUI node Pillar_For_ComfyUI 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.
- Base VRAM:
- 128MB (0.1GB)
- Recommended GPU:
- 4GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- MEDIUM
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 Pillar_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 Pillar_For_ComfyUI?
Direct Answer: Running Pillar_For_ComfyUI requires installing the following Python package dependencies: fastapi, huggingface_hub, langdetect, pillow, pydantic, requests, torch, torchvision, transformers. Ensure your ComfyUI environment has these packages active before launching.
fastapi
huggingface_hub
langdetect
pillow
pydantic
requests
torch
torchvision
transformersInteractive Setup & Dependency Resolver
# Loading command...Frequently Asked Questions
How much VRAM does Pillar_For_ComfyUI require?
Pillar_For_ComfyUI 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 Pillar_For_ComfyUI 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
How much VRAM does Pillar_For_ComfyUI take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), Pillar_For_ComfyUI runs smoothly on an RTX 3060 (12GB) with 10.7GB 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 21.5GB 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 Pillar_For_ComfyUI need?
Pillar_For_ComfyUI requires the following PyTorch-related packages: torch, torchvision. 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 Pillar_For_ComfyUI?
To run Pillar_For_ComfyUI, you need to install: fastapi, huggingface_hub, langdetect, pillow, pydantic, requests, torch, torchvision, transformers. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running Pillar_For_ComfyUI?
Pillar_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 Pillar_For_ComfyUI in ComfyUI?
To install Pillar_For_ComfyUI: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/aicoder-max/Pillar_For_ComfyUI, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.