ComfyUI_Face_similarity

A custom ComfyUI node that compares face identity between two images using InsightFace embeddings. Useful for verifying that a generated image preserves the identity of a reference person.

Quick Technical Summary: ComfyUI_Face_similarity

Base VRAM Footprint:
128 MB (4 GB Tier)
Primary Dependencies:
insightface>=0.7.3, numpy>=1.24.0, onnxruntime-gpu>=1.16.0, opencv-python>=4.8.0
Min PyTorch / CUDA:
PyTorch 2.0+ | CUDA 12.1+
GitHub Repository:
https://github.com/phobod/ComfyUI_Face_similarity

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

How much VRAM does ComfyUI_Face_similarity require?

Direct Answer: The ComfyUI node ComfyUI_Face_similarity 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.

High (2-4GB)
Base VRAM:
128MB (0.1GB)
Recommended GPU:
4GB+ VRAM
Low VRAM Mode:
✓ Supported
Estimation Confidence:
MEDIUM

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 ComfyUI_Face_similarity? 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 ComfyUI_Face_similarity:

Live Cloud Deploy Options

Live Market Rates

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

What Python packages are required for ComfyUI_Face_similarity?

Direct Answer: Running ComfyUI_Face_similarity requires installing the following Python package dependencies: insightface>=0.7.3, numpy>=1.24.0, onnxruntime-gpu>=1.16.0, opencv-python>=4.8.0. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
insightface>=0.7.3
numpy>=1.24.0
onnxruntime-gpu>=1.16.0
opencv-python>=4.8.0

Interactive Setup & Dependency Resolver

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

Universal Architecture Compatibility

ComfyUI_Face_similarity 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 ComfyUI_Face_similarity require?

ComfyUI_Face_similarity 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 ComfyUI_Face_similarity 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 ComfyUI_Face_similarity take on an RTX 3060 vs RTX 4090?

On an RTX 3060 (12GB VRAM), ComfyUI_Face_similarity 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 Python packages are required for ComfyUI_Face_similarity?

To run ComfyUI_Face_similarity, you need to install: insightface>=0.7.3, numpy>=1.24.0, onnxruntime-gpu>=1.16.0, opencv-python>=4.8.0. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ComfyUI_Face_similarity?

ComfyUI_Face_similarity 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 ComfyUI_Face_similarity in ComfyUI?

To install ComfyUI_Face_similarity: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/phobod/ComfyUI_Face_similarity, (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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