Updated: Jun 3, 2026
base model
🌟 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.
⚙️ Recommended Generation Settings
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 trained LoRAs are officially supported.
✅ Z-Image-Base trained LoRAs: Work flawlessly.
❓ Z-Image-Turbo trained 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