wlsh_nodes

By wallish77View on GitHub →

Nodes: Checkpoint Loader with Name, Save Prompt Info, Outpaint to Image, CLIP Positive-Negative, SDXL Quick Empty Latent, Empty Latent by Ratio, Time String, SDXL Steps, SDXL Resolutions ...

Quick Technical Summary: wlsh_nodes

Base VRAM Footprint:
8192 MB (12 GB Tier)
Primary Dependencies:
piexif
Min PyTorch / CUDA:
PyTorch 2.0+ | CUDA 12.1+
GitHub Repository:
https://github.com/wallish77/wlsh_nodes

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

How much VRAM does wlsh_nodes require?

Direct Answer: The ComfyUI node wlsh_nodes requires a minimum base VRAM of 8192MB and is optimized for GPUs with at least 12GB of VRAM. Low VRAM mode is not supported for this node.

Very High (4-8GB)
Base VRAM:
8192MB (8.0GB)
Recommended GPU:
12GB+ VRAM
Low VRAM Mode:
✗ Not supported
Estimation Confidence:
HIGH

Cheapest VRAM Upgrade Paths (Live Market Prices):

  • GeForce RTX 3060 12GB (Budget 12GB Upgrade)──► Used: $209.62View eBay ↗
  • GeForce RTX 4070 12GB (High-Performance 12GB)──► New: $535.75View Amazon ↗

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!

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 wlsh_nodes:

Live Cloud Deploy Options

Live Market Rates

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

Buy NVIDIA GeForce RTX 4070 (12GB VRAM)

Tired of renting cloud rigs? Run ComfyUI locally with absolute zero latency. The sweet spot for Stable Diffusion XL (SDXL) and quantized FLUX.1 (FP8/GGUF) workflows.

🛒 Buy on Amazon
calculate

Local GPU Upgrade vs. Cloud Rental

Compare the real financial break-even point for ComfyUI generation.

10 hours / week

shopping_cartBuy NVIDIA GeForce RTX 4070

Card Purchase Price:
$540.00
Active Wattage Draw:
200 Watts
Annual Electric Cost:
$0.00
Buy Local GPU on Amazon

cloudRent GPU On-Demand

Estimated Cloud Rate:
$0.22 / hr
Weekly Cloud Billing:
$0.00
Annual Cost (Equivalent):
$0.00
Deploy Instantly in Cloud

Financial Break-Even Point

You need to run workflows for ...

before upgrading local hardware becomes more economical than renting cloud compute.

Are you the author of this node?

Help your users avoid out-of-memory errors by displaying this professional, dynamic VRAM badge on your GitHub README. Copy the markdown below to embed it with a backlink directly to this hardware specification profile.

Live Preview:VRAM DB Badge
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[![VRAM Specs](https://vramdb.com/badge/wallish77/wlsh_nodes.svg)](https://vramdb.com/nodes/wallish77/wlsh_nodes/)

What Python packages are required for wlsh_nodes?

Direct Answer: Running wlsh_nodes requires installing the following Python package dependencies: piexif. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
piexif

Interactive Setup & Dependency Resolver

Operating System:
Environment Type:
Run this terminal command in your ComfyUI root folder:
# Loading command...

Compatible Foundations

This node is verified to support or optimize workflows for the following foundation model families:

Frequently Asked Questions

How much VRAM does wlsh_nodes require?

wlsh_nodes requires a minimum of 8192MB (8.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 12GB of VRAM is recommended. Low VRAM mode is not supported for this node.

Can I run wlsh_nodes on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 2.8GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 2.8GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 6.4GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 13.6GB headroom

How much VRAM does wlsh_nodes take on an RTX 3060 vs RTX 4090?

On an RTX 3060 (12GB VRAM), wlsh_nodes runs smoothly on an RTX 3060 (12GB) with 2.8GB 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 13.6GB 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 Python packages are required for wlsh_nodes?

To run wlsh_nodes, you need to install: piexif. You can install these using pip or add them to your requirements.txt file.

How do I install wlsh_nodes in ComfyUI?

To install wlsh_nodes: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/wallish77/wlsh_nodes, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.