ComfyUI_Gemini3ProImagePreview

By Ametist3dView on GitHub →

NanoBanana2 is a custom ComfyUI node for Google Gemini image generation models.

How much VRAM does ComfyUI_Gemini3ProImagePreview require?

Direct Answer: The ComfyUI node ComfyUI_Gemini3ProImagePreview 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!

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What Python packages are required for ComfyUI_Gemini3ProImagePreview?

Direct Answer: Running ComfyUI_Gemini3ProImagePreview requires installing the following Python package dependencies: google-generativeai>=0.8.0, numpy>=1.24.0, pillow>=10.0.0, requests>=2.31.0, torch>=2.0.0. This node specifically requires PyTorch version 2.0.0 or newer.

requirements.txt
google-generativeai>=0.8.0
numpy>=1.24.0
pillow>=10.0.0
requests>=2.31.0
torch>=2.0.0

Interactive Setup & Dependency Resolver

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

Special Environment Requirements:

Requires PyTorch version 2.0.0+.

To update PyTorch for your selected setup, run:
# Loading PyTorch command...

Related Custom Nodes

The following custom nodes run in the same PyTorch / CUDA environment and share similar categories or workflows:

ComfyUI Colormaster Nodes
by orion4d128MB VRAM
ComfyUI LoRA Block Weight Loader
by bhvbhushan128MB VRAM
ComfyUI SKBundle
by SKBv0256MB VRAM
ComfyUI-BGPSeg
by PozzettiAndrea128MB VRAM

Frequently Asked Questions

How much VRAM does ComfyUI_Gemini3ProImagePreview require?

ComfyUI_Gemini3ProImagePreview 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 ComfyUI_Gemini3ProImagePreview 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

What PyTorch version does ComfyUI_Gemini3ProImagePreview need?

ComfyUI_Gemini3ProImagePreview requires the following PyTorch-related packages: torch>=2.0.0. Ensure your ComfyUI environment has these installed. Ensure your PyTorch installation matches your CUDA version (use torch.version.cuda to check).

What Python packages are required for ComfyUI_Gemini3ProImagePreview?

To run ComfyUI_Gemini3ProImagePreview, you need to install: google-generativeai>=0.8.0, numpy>=1.24.0, pillow>=10.0.0, requests>=2.31.0, torch>=2.0.0. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running ComfyUI_Gemini3ProImagePreview?

ComfyUI_Gemini3ProImagePreview 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_Gemini3ProImagePreview in ComfyUI?

To install ComfyUI_Gemini3ProImagePreview: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/Ametist3d/ComfyUI_Gemini3ProImagePreview, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.