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wbruna/Z-Image-Turbo-sdcpp-GGUF
Z-Image-Turbo-sdcpp-GGUF is a text-to-image model from wbruna. Use it when you need an image from a text prompt. The card lists the license as apache-2.0.
Quantized GGUF versions of the Z-Image Turbo model by Tongyi-MAI, for use with stable-diffusion.cpp.
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From the Hugging Face model README
Quantized GGUF versions of the Z-Image Turbo model by Tongyi-MAI, for use with stable-diffusion.cpp.
These are legacy, experimental quants. See https://huggingface.co/leejet/Z-Image-Turbo-GGUF for the official stable-diffusion.cpp quants.
For k-quants to use with ComfyUI, see https://huggingface.co/jayn7/Z-Image-Turbo-GGUF .
You can recreate these locally from the original files with something like:
./sd --mode convert --type q5_1 --model z_image_turbo_bf16.safetensors --output z_image_turbo-Q5_1.gguf
See the original model card at Z-Image Turbo.
You need at least release master-385-34a6fd4.
Example command:
./sd --diffusion-model z_image_turbo-Q5_1.gguf --vae ae_bf16.safetensors --llm qwen_3_4b-Q8_0.gguf --cfg-scale 1 --steps 8 -p "an apple"
For lower quality, faster generations, you can use euler + sgm_uniform with very few steps, and/or TAE:
./sd --diffusion-model z_image_turbo-Q4_0.gguf --tae taef1.safetensors --llm qwen_3_4b-Q8_0.gguf --cfg-scale 1 --steps 5 --sampling-method euler --scheduler sgm_uniform -p "an apple"
ae_bf16.safetensors from https://huggingface.co/Tongyi-MAI/Z-Image-Turbo/tree/main/vaetaef1.safetensors from https://huggingface.co/madebyollin/taef1/tree/mainApache 2.0, same as the original: Z-Image Turbo.