comfyui_davcha
Nodes:SmartMask, ResizeCropFit, Percent Padding, SoftErosion, StringScheduleHelper, DStack, DavchaConditioningConcat, DavchaModelMergeSimple, DavchaCLIPMergeSimple, DavchaModelMergeSD1, DavchaModelMergeSDXL, ConditioningCompress... Some personal QoL and experimental nodes
Quick Technical Summary: comfyui_davcha
- Base VRAM Footprint:
- 8192 MB (12 GB Tier)
- Primary Dependencies:
- rapidfuzz, webp
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/dchatel/comfyui_davcha
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does comfyui_davcha require?
Direct Answer: The ComfyUI node comfyui_davcha 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.
- 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
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 comfyui_davcha:
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.
Local GPU Upgrade vs. Cloud Rental
Compare the real financial break-even point for ComfyUI generation.
Buy NVIDIA GeForce RTX 4070
- Card Purchase Price:
- $540.00
- Active Wattage Draw:
- 200 Watts
- Annual Electric Cost:
- $0.00
Rent GPU On-Demand
- Estimated Cloud Rate:
- $0.22 / hr
- Weekly Cloud Billing:
- $0.00
- Annual Cost (Equivalent):
- $0.00
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.
What Python packages are required for comfyui_davcha?
Direct Answer: Running comfyui_davcha requires installing the following Python package dependencies: rapidfuzz, webp. Ensure your ComfyUI environment has these packages active before launching.
rapidfuzz
webpInteractive Setup & Dependency Resolver
# Loading command...Frequently Asked Questions
How much VRAM does comfyui_davcha require?
comfyui_davcha 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 comfyui_davcha 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 comfyui_davcha take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), comfyui_davcha 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 comfyui_davcha?
To run comfyui_davcha, you need to install: rapidfuzz, webp. You can install these using pip or add them to your requirements.txt file.
How do I install comfyui_davcha in ComfyUI?
To install comfyui_davcha: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/dchatel/comfyui_davcha, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.