You may have noticed that the Z-Image-Turbo model doesn't produce a lot of variety when varying seeds. This native workflow is an attempt to generate more variety by starting encoding with an SD 1.5 model. Z-Image...
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You may have noticed that the Z-Image-Turbo model doesn't produce a lot of variety when varying seeds. This native workflow is an attempt to generate more variety by starting encoding with an SD 1.5 model. Z-Image still does most of the work, and at the end, so I'm calling my use of SD 1.5 a "prefiner".
The prefiner adds variety to everything, but the un-described background seems most affected. While SD 1.5 generates a 512x512 image, there appears to be no problem with resizing the result to most shapes for final generation.
A few notes after 24 hours:
My favorite scheduler for Z-Image is now sgm-uniform, rather than the workflow default.
Turning up the CFG on SD 1.5 can reduce, but not remove, the patterns all over the place.
AI-generated commentary
AI-generated explanation based on source and configuration details. Suggestions are clearly labeled.
Z-Image SD variety prefiner is for trying to generate more varied Z-Image-Turbo images: it starts encoding with SD 1.5, uses Z-Image-Turbo for most of the work and the final stage, takes a seed you can vary, and outputs an image.
SD 1.5 starts the encoding, while Z-Image-Turbo does most of the work and handles the final stage.
The description says the prefiner adds variety across the image, with the undescribed background seeming most affected.
The SD 1.5 stage generates a 512×512 image, and the author notes that it can be resized to most shapes for final generation.
A SaveImage step is listed in the workflow.
Published by Ken G6 on Civitai at https://civitai.com/models/2172045.
The listed model files are ae.safetensors, hddclip/qwen_3_4b.safetensors, sd15/realisticVisionV51_v51VAE.safetensors, and z_image_turbo_bf16.safetensors.
Listed node types include CheckpointLoaderSimple, CLIPLoader, CLIPTextEncode, EmptySD3LatentImage, KSamplerAdvanced, LatentUpscale, and ModelSamplingAuraFlow.
Other listed node types are PrimitiveInt, PrimitiveStringMultiline, SaveImage, UNETLoader, VAEDecode, VAEEncode, and VAELoader.
The author lists sgm-uniform as a preferred Z-Image scheduler instead of the workflow default.
Increasing SD 1.5 CFG can reduce patterns across the image, but not eliminate them.
A relatively high step break of 2 or 3 can sometimes produce a cartoony look, but the described effect is not reliably repeatable.
No license is listed for this workflow; review the Civitai page before reuse.
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Before using it, confirm that your setup has the listed model files and node types.
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Sources
1 sourceSource excerpts
1 excerptSource context: 143 downloads · Type Workflows · Base model ZImageTurbo
Occasionally, a relatively high step break of 2 or 3 has the effect of turning the whole image cartoony. It's a nice effect but I can't do it reliably yet.
Estimated VRAM requirement
Estimate unavailable
11.8 GB across 2 of 9 model files. Model file total + 25% loading overhead + 2 GB execution buffer, rounded up.
Requirements
18 requirementsae.safetensors
FoundVAE · 320 MB · SAFETENSORS · Unknown
CLIPLoader
PossibleText encoder · Unknown
Text encoder · Hugging Face · hddclip/qwen_3_4b.safetensors · Z Image Turbo (Turbo)
LatentUpscale
PossibleUpscaler · Unknown
sd15/realisticVisionV51_v51VAE.safetensors
Not resolvedVAE · Hugging Face · sd15/realisticVisionV51_v51VAE.safetensors
VAEDecode
PossibleVAE · Unknown
VAEEncode
PossibleVAE · Unknown
VAELoader
PossibleVAE · Unknown
Checkpoint · 11.5 GB · SAFETENSORS · bf16 · Unknown
CheckpointLoaderSimple
PossibleNode pack · Unknown
CLIPTextEncode
PossibleNode pack · Unknown
EmptySD3LatentImage
Not resolvedNode pack · Unknown
Node pack · Unknown
Node pack · Unknown
PrimitiveInt
Not resolvedNode pack · Unknown
PrimitiveStringMultiline
Not resolvedNode pack · Unknown
SaveImage
PossibleNode pack · Unknown
UNETLoader
PossibleNode pack · Unknown