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ChrisColeTech/
z-image-turbo-GGUF

Name: z-image-turbo-GGUF
Availability: InStock

Tongyi-MAI/Z-Image-Turbo

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Z-Image Turbo — GGUF build

6B text-to-image, distilled for a 9-step CFG-free profile. Repacked as a split GGUF layout.

What this repo is: a requantized, split-layout build of the upstream model — weights only, not a retrain. The recommended settings below are the values these weights are actually run with day to day, not copied from the upstream card.

Samples

prompt: a red apple on a rustic wooden table beside a window, soft daylight, visible wood grain, studio photograph, sharp focus — 1024×1024, 9 steps, guidance 0.0, seed 7	prompt: portrait of an older fisherman with a weathered face, natural window light, shallow depth of field, photorealistic — 1024×1024, 9 steps, guidance 0.0, seed 99
_{prompt: `a red apple on a rustic wooden table beside a window, soft daylight, visible wood grain, studio photograph, sharp focus` — 1024×1024, 9 steps, guidance 0.0, seed 7}	_{prompt: `portrait of an older fisherman with a weathered face, natural window light, shallow depth of field, photorealistic` — 1024×1024, 9 steps, guidance 0.0, seed 99}
prompt: a rain-slicked Tokyo street at night, neon signs reflecting in puddles, cinematic, 35mm photograph — 1024×1024, 9 steps, guidance 0.0, seed 1234
_{prompt: `a rain-slicked Tokyo street at night, neon signs reflecting in puddles, cinematic, 35mm photograph` — 1024×1024, 9 steps, guidance 0.0, seed 1234}

img2img

This model does img2img as well as txt2img. The left image is the input; the right is what this model made of it.

source prompt: a red apple on a rustic wooden table beside a window, soft daylight, visible wood grain, studio photograph, sharp focus — 1024×1024, seed 7 — generated separately as the img2img input	img2img prompt: the same scene rendered as a vivid oil painting, thick visible brushstrokes, rich saturated colour, painterly texture — 1024×1024, 9 steps, strength 0.9, seed 7 — about 6 s on an A100 80GB
_{source prompt: `a red apple on a rustic wooden table beside a window, soft daylight, visible wood grain, studio photograph, sharp focus` — 1024×1024, seed 7 — generated separately as the img2img input}	_{img2img prompt: `the same scene rendered as a vivid oil painting, thick visible brushstrokes, rich saturated colour, painterly texture` — 1024×1024, 9 steps, strength 0.9, seed 7 — about 6 s on an A100 80GB}

strength has a hard threshold on this model. A sweep at 0.3 / 0.5 / 0.7 / 0.9 — same source, prompt and seed — produced no meaningful restyle below 0.9; those values add gloss and surface detail and leave the photograph a photograph. The painterly transform appears only at 0.9. Treat it as near-binary rather than a dial: 0.9 to restyle, low values only for a light finishing pass.

Recommended settings

Values this build is run with in practice. They are read out of a live config when this card is generated, so they cannot drift from what is actually used.

Parameter	Production value	Meaning
`width`	`1024`	Output width in pixels
`height`	`1024`	Output height in pixels
`steps`	`9`	Denoising steps
`guidance`	`0.0`	Guidance scale
`preview_every`	`3`	Emit a TAESD preview every N steps
`strength`	`0.9`	img2img denoise strength (1.0 = ignore the input image)

Supported modes: txt2img, img2img

Notes and gotchas

Guidance is 0.0, not 1.0. Z-Image Turbo is a guidance-distilled turbo model; this build expects guidance=0.0 and any positive CFG fights the distillation.
Text encoder is Qwen3-VL-4B, not the encoder in the original upstream layout. The transformer file also carries a -fresh suffix; both are reflected in the paths below.
9 steps at 1024² is the verified profile for this build.

Layout

Components ship as separate files rather than one bundle: the transformer, the text encoder(s) and the VAE each load independently, with configs and tokenizers under config/. Any loader that accepts explicit per-component paths can consume this directly — point it at the files listed below.

A generic diffusers snippet is deliberately omitted. This is a repacked split layout with substituted encoders, so an upstream example will not load it unmodified, and an untested snippet would be worse than none.

Files

File	Size	Role
`split/z-image-turbo-q6k-fresh.gguf`	4.71 GB	transformer (main weights)
`split/text_encoders/Qwen3-VL-4B-Q4_K_M.gguf`	2.32 GB	text encoder
`split/vae/ae.safetensors`	319.77 MB	VAE
`config/tokenizer/tokenizer.json`	6.71 MB	tokenizer / processor
`config/tokenizer/vocab.json`	2.65 MB	tokenizer / processor
`config/tokenizer/merges.txt`	1.59 MB	tokenizer / processor
`config/tokenizer/tokenizer_config.json`	9.50 KB	tokenizer / processor
`config/vae/config.json`	805 B	VAE
`config/text_encoder/config.json`	726 B	text encoder
`config/controlnet/config.json`	542 B	config
`config/transformer/config.json`	473 B	transformer (main weights)
`config/model_index.json`	467 B	config
`config/scheduler/scheduler_config.json`	173 B	scheduler config

Provenance

Upstream base model: Tongyi-MAI/Z-Image-Turbo (upstream license: apache-2.0)
This build: requantized and relaid out into a split component layout. Weights are not retrained; only the format and directory layout differ.
License: left as unknown in this repo's metadata. Refer to the upstream model's license for redistribution and commercial-use terms — several of these bases are non-commercial.

ChrisColeTech/z-image-turbo-GGUF