Krea-R-Turbo

Link to Model:
https://huggingface.co/realrebelai/Krea-R-Turbo/tree/main

Test the model on HF Spaces for free:
https://huggingface.co/spaces/realrebelai/Krea-R-Turbo

Full Weight and GGUF quants of custom merge of Krea-2-Turbo and 2 of my style LoRAs at specific strength values. Displays a heavy focus on photorealistic portraits to achieve high grade aesthetics while also retaining Krea-2s sharp detail!

This is a derivative of krea/Krea-2-Turbo: LoRA-merged, then quantized. It is not the original checkpoint.

Quants

Pick by how much VRAM you can spare for the diffusion model (leave room for the text encoder + VAE). Sizes are approximate — see the Files tab for exact numbers.

FileType~SizeNotes

Krea-R-Turbo-Q8_0.gguf Q8_0~14 GB Near-lossless. For 16 GB+ cards or offload.

Krea-R-Turbo-Q6_K.ggufQ6_K~11 GBExcellent quality, hard to tell from Q8.

Krea-R-Turbo-Q5_K_M.ggufQ5_K_M~9.4 GBGreat quality/size balance.

Krea-R-Turbo-Q4_K_M.ggufQ4_K_M~8.0 GB Recommended all-rounder. 12 GB cards, or 8 GB with offload.

Krea-R-Turbo-Q3_K_M.ggufQ3_K_M~6.4 GBBest pick for 8 GB VRAM. Small quality trade.

Krea-R-Turbo-Q2_K.ggufQ2_K~5.5 GBTightest fit. Visible degradation but usable.

On an 8 GB card (e.g. RTX 3070), Q3_K_M or Q2_K fit most comfortably alongside the VAE and text encoder. Larger quants still run via ComfyUI's --lowvram / block-swap offload — just slower.

Usage in ComfyUI

Place the files:

FileFolderKrea-R-Turbo-QX.gguf (this repo)ComfyUI/models/unet/ (or diffusion_models/)qwen3vl_4b text encoderComfyUI/models/text_encoders/qwen_image_vae.safetensorsComfyUI/models/vae/

The text encoder (Qwen3-VL 4B) and VAE (Qwen-image VAE) are the standard Krea 2 companions and can be pulled from the ComfyUI repack: Comfy-Org/Krea-2.

Wire it up: load the GGUF with the Unet Loader (GGUF) node, feed it the Qwen3-VL text encoder and Qwen-image VAE, and sample as normal Krea 2 Turbo.

Recommended sampling

Krea 2 Turbo is a distilled, few-step model:

• Steps: ~8

• Guidance: CFG-free — set CFG to 1.0 (no negative prompt), or guidance 0

• Sampler / scheduler: er_sde + simple works well (or euler + simple)

• Resolution: up to 2048², 1024–1280 sweet spot on 8 GB

No positive/negative CFG split is needed; this checkpoint was distilled without it.

Requirements

• ComfyUI (recent build with Krea 2 support)

• RealRebelAI/ComfyUI-GGUF_KREA-2 custom node

• Qwen3-VL 4B text encoder + Qwen-image VAE (from Comfy-Org/Krea-2)

This repo contains the diffusion model (transformer) only — it will not generate anything on its own without the VAE and text encoder above.

License & attribution

These weights are a derivative of Krea 2 Turbo © Krea.ai, Inc., and remain governed by the Krea 2 Community License Agreement and the Krea Acceptable Use Policy — exactly as the original model. See the license: LICENSE.pdf. In the event of any conflict, the Krea Acceptable Use Policy and Krea 2 Community License control.

Deployer obligation: if you serve or redistribute this model, the license requires you to implement content-filtering or equivalent review to prevent generation or distribution of unlawful or policy-violating content. Report harmful or illegal outputs to [email protected].

Upstream:

• Base model: krea/Krea-2-Turbo (distilled from krea/Krea-2-Raw)

• ComfyUI repack (VAE / text encoder): Comfy-Org/Krea-2

• GGUF tooling based on city96's ComfyUI-GGUF

The merge and quantization are RealRebelAI's work; the underlying model rights belong to Krea.ai, Inc.

Credits

Merged, quantized, and released by RealRebelAI.

• GitHub: github.com/RealRebelAI

• Hugging Face: huggingface.co/realrebelai

If these are useful, a like on the repo helps others find them. Issues with loading go on the ComfyUI-GGUF_KREA-2 tracker.