Text Encode (Krea2)

By ethanfelView on GitHub →

Vision-aware text conditioning for the Krea2 / K2 model. Feeds reference images through the Qwen3-VL-4B vision path with the Krea2 descriptor template; optional per-image mask crops to the masked region. No VAE (Krea2 has no reference-latent pathway). Auto-growing image+mask slots.

How much VRAM does Text Encode (Krea2) require?

Direct Answer: The ComfyUI node Text Encode (Krea2) 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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Related Custom Nodes

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

AITocha Vision
by aitocha128MB VRAM
AI_Text_Comfyui
by Zch6111256MB VRAM
AK XZ Axis (XY for any KSampler)
by akawana256MB VRAM
ArtyClaw Comfy Nodes
by artyclaw256MB VRAM

Frequently Asked Questions

How much VRAM does Text Encode (Krea2) require?

Text Encode (Krea2) 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 Text Encode (Krea2) 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

How can I reduce VRAM usage when running Text Encode (Krea2)?

Text Encode (Krea2) 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 Text Encode (Krea2) in ComfyUI?

To install Text Encode (Krea2): (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/ethanfel/ComfyUI-Krea2TextEncoder, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.