comfyui-gemma4translate-e2b

By jkmq-fView on GitHub →

ComfyUI custom node for local translation with Gemma 4 E2B

How much VRAM does comfyui-gemma4translate-e2b require?

Direct Answer: The ComfyUI node comfyui-gemma4translate-e2b 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!

Deploy on High-Performance GPUs

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🚀 Deploy on Vast.ai

Deploy on Cloud GPUs

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What Python packages are required for comfyui-gemma4translate-e2b?

Direct Answer: Running comfyui-gemma4translate-e2b requires installing the following Python package dependencies: accelerate>=1.0.0,<2.0, bitsandbytes>=0.43.0,<1.0 ; platform_system == "Linux", huggingface_hub>=0.30.0,<1.0, langcodes>=3.4.0,<4.0, pillow>=10.0.0,<12.0, sentencepiece>=0.2.0,<1.0, transformers==5.5.0, wheel==0.45.1. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
accelerate>=1.0.0,<2.0
bitsandbytes>=0.43.0,<1.0 ; platform_system == "Linux"
huggingface_hub>=0.30.0,<1.0
langcodes>=3.4.0,<4.0
pillow>=10.0.0,<12.0
sentencepiece>=0.2.0,<1.0
transformers==5.5.0
wheel==0.45.1

Interactive Setup & Dependency Resolver

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

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AITocha Vision
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AK XZ Axis (XY for any KSampler)
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ArtyClaw Comfy Nodes
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Frequently Asked Questions

How much VRAM does comfyui-gemma4translate-e2b require?

comfyui-gemma4translate-e2b 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-gemma4translate-e2b 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

What Python packages are required for comfyui-gemma4translate-e2b?

To run comfyui-gemma4translate-e2b, you need to install: accelerate>=1.0.0,<2.0, bitsandbytes>=0.43.0,<1.0 ; platform_system == "Linux", huggingface_hub>=0.30.0,<1.0, langcodes>=3.4.0,<4.0, pillow>=10.0.0,<12.0, sentencepiece>=0.2.0,<1.0, transformers==5.5.0, wheel==0.45.1. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running comfyui-gemma4translate-e2b?

comfyui-gemma4translate-e2b 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-gemma4translate-e2b in ComfyUI?

To install comfyui-gemma4translate-e2b: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/jkmq-f/ComfyUI-Gemma4Translate-E2B, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.