Auto Crop By NPS
A very useful automatic cropping tool! It can realize cropping, expansion and rotation functions in the form of a slider.
Quick Technical Summary: Auto Crop By NPS
- Base VRAM Footprint:
- 256 MB (4 GB Tier)
- Primary Dependencies:
- None (Pure Python/Torch)
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/WX-NPS1598/ComfyUI-Auto_Crop_By_NPS
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does Auto Crop By NPS require?
Direct Answer: The ComfyUI node Auto Crop By NPS 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 Auto Crop By NPS:
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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Frequently Asked Questions
How much VRAM does Auto Crop By NPS require?
Auto Crop By NPS 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 Auto Crop By NPS 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 Auto Crop By NPS take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), Auto Crop By NPS 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.
How can I reduce VRAM usage when running Auto Crop By NPS?
Auto Crop By NPS 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 Auto Crop By NPS in ComfyUI?
To install Auto Crop By NPS: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/WX-NPS1598/ComfyUI-Auto_Crop_By_NPS, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.