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Image Edit ​

Inpainting, image-to-image, and regional editing setups built on Fibo 2.0, Flux 3 Klein, Qwen Image 2.1 Turbo, Qwen Image 2.1, Ideogram 4, and Krea 2 GGUF quants.

Inpainting ​

Encode the source image to latent space with the VAE. Feed a mask into the sampler so only the masked region regenerates. Decode the result back to pixel space.

Image-to-image ​

Encode the source image to latent space. Run the sampler with a controlled strength so the output stays close to the input. Decode the result.

Regional editing ​

Chain a mask into the conditioning stage. The GGUF diffusion model regenerates only the selected region and leaves the rest of the latent unchanged.

Models and formats ​

ModelRepositoryRecommended formats
Fibo 2.0 Devmolbal/fibo-2.0-GGUFQ8_CR, Q8_0, Q6_K, Q4_K_M
Fibo 2.0 Edit Turbomolbal/fibo-2.0-GGUFQ8_CR, Q8_0, Q6_K, Q4_K_M
Flux 3 Kleinmolbal/Flux-3-Klein-GGUFQ8_CR, Q8_0, Q6_K, Q4_CR_L, Q4_K_M
Ideogram 4molbal/ideogram-4-ggufQ8_CR, Q8_0
Krea 2molbal/krea2-ggufQ8_0, Q4_K_M
Qwen Image 2.1 Turbomolbal/Qwen-Image-2.1-Turbo-GGUFQ8_CR, Q8_0, Q6_K, Q4_K_M
Qwen Image 2.1molbal/Qwen-Image-2.1-GGUFQ8_CR, Q8_0

Loading instructions ​

  1. Download the GGUF files from Hugging Face.
  2. Load the diffusion model and text encoder with the GGUF loader nodes from comfyui-gguf-reboot.
  3. Encode the source image with the VAE before sampling.
  4. For inpainting and regional edits, feed the mask into the sampler.
  5. Decode the result.

Showcase ​

Image examples are on molbal's Civitai profile.

GGUF quantization and open-source tools.