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ZIT-Prism

Updated: May 17, 2026

base model

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qwen_3_4b_fp8_mixed.safetensors5.25 GB

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Type

Checkpoint Trained

Stats

170

Reviews

Published

May 17, 2026

Base Model

ZImageBase

Hash

AutoV2
2F9DB9446B
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Cryhell's Avatar

Cryhell

License:

Apache 2.0

🌟 ZIT-PRISM

The uncompromising power of Base, packed into the lightning speed of Turbo.


ZIT-Prism (Z-Image-Turbo Prism) is a custom fine-tuned and fully distilled derivative of the Z-Image-Base model. If you love the deep prompt adherence, complex textures, and high-fidelity details of the Base model but hate waiting for 30–50 steps, this is the model for you.

By carefully fine-tuning and distilling the Base architecture, ZIT-Prism achieves stunning, production-ready generations in just 8 steps.


✨ Why use ZIT-Prism?

  • Best of Both Worlds: Retains the rich compositional intelligence and aesthetics of Z-Image-Base while generating at the speed of Z-Image-Turbo.


To get the absolute best results out of this distilled model, please use the following parameters:

  • Steps: 8

  • CFG Scale: 1.0

  • Sampler: Euler / Euler a

Feel free to experiment!


🧩 LoRA Compatibility (Important!)

Because ZIT-Prism is fundamentally built on the Base architecture (despite its Turbo-like speed), only Z-Image-Base LoRAs are officially supported.

  • Z-Image-Base LoRAs: Work flawlessly.

  • Z-Image-Turbo LoRAs: You can certainly give them a try, but results may be unpredictable or deep-fried due to the conflicting distillation methods.


💬 Prompting Advice

ZIT-Prism thrives on both natural language prompting and tags as the model Z-Image was trained with both!

As per this paper by Tongyi-MAI - creator of Z-Image: Paper page - Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer


Any support you can give will very much be appreciated, as they will help me in my future endeavors as a creator, and also as a college student: https://ko-fi.com/ppoyaa