Aspect Ratio Size Picker

By EternalShade3DView on GitHub →

A single, no-nonsense node to pick text-to-image dimensions from an aspect-ratio dropdown, a long-edge slider, and an invert toggle. Outputs width/height (INT) plus an info STRING that previews the resolved size, orientation and common long-edge reference sizes.

Quick Technical Summary: Aspect Ratio Size Picker

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/EternalShade3D/ComfyUI-AspectRatioSizePicker

Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.

How much VRAM does Aspect Ratio Size Picker require?

Direct Answer: The ComfyUI node Aspect Ratio Size Picker 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.

High (2-4GB)
Base VRAM:
256MB (0.3GB)
Recommended GPU:
4GB+ VRAM
Low VRAM Mode:
✓ Supported
Estimation Confidence:
HIGH

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!

⚡

Struggling with VRAM Crashes or Out-of-Memory Errors?

Running heavy models like FLUX or SDXL with Aspect Ratio Size Picker? If you experience torch.cuda.OutOfMemoryError or driver timeouts, read our comprehensive troubleshooting guide to configure launch flags, enable tiled decoding, and avoid crashes.

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 Aspect Ratio Size Picker:

Live Cloud Deploy Options

Live Market Rates

Run this node in cloud environments with pre-configured CUDA/PyTorch dependencies:

No Python Dependencies Required

This node runs purely on native ComfyUI python contexts. No external pip libraries require automated installation!

Universal Architecture Compatibility

Aspect Ratio Size Picker operates as a general-purpose processor without binding directly to a single checkpoint architecture. It can be paired across Stable Diffusion 1.5, SDXL, FLUX, and video diffusion pipelines.

Frequently Asked Questions

How much VRAM does Aspect Ratio Size Picker require?

Aspect Ratio Size Picker 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 Aspect Ratio Size Picker 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 Aspect Ratio Size Picker take on an RTX 3060 vs RTX 4090?

On an RTX 3060 (12GB VRAM), Aspect Ratio Size Picker 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 Aspect Ratio Size Picker?

Aspect Ratio Size Picker 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 Aspect Ratio Size Picker in ComfyUI?

To install Aspect Ratio Size Picker: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/EternalShade3D/ComfyUI-AspectRatioSizePicker, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.

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