Sign In

CyberRealistic Z-Image Turbo Catalyst

4.8k

Download

1 variant available

bf16 SafeTensor

CyberRealistic_zit_catalyst_v2.0.safetensors

BF16, good balance • 11.7 GB

Verified:

You need these files to run this model. We'll show the best match for your preferences.

Z Image Turbo
VAE
External

Turboae_zimgturbo.safetensors

319.77 MB

Z Image Turbo
Text Encoder
External

Turboqwen_3_4b.safetensors

7.49 GB

Downloads your preferred variants

Type
Checkpoint Trained
Stats

1,075

4K

14.7K

Reviews
Published

Jul 4, 2026

Base Model

ZImageTurbo

Hash
AutoV2
A46A82A99E
default creator card background decoration
Followers - 23239

23.2K

Downloads - 2409062

2.4M

Generations - 80388804

80.4M

Forge Badge

License:

Apache 2.0
200104_00000.png

Join The Tinkerer on Whop. Membership gets you early releases, private tools and a bunch of extra stuff.

👉 Join on Whop
💬 Join the community for support, free tools and early news on Discord


CyberRealistic Z-Image Turbo Catalyst is part of the Catalyst experimental line - a dedicated space for targeted experiments that go beyond.

This build focuses on three specific areas:

  • Character LoRA compatibility: better integration and less drift

  • Skin & color rendering: refined skin tones and overall color behavior

  • Bug fixes: corrections for known issues

Why Catalyst and not a new Z-Image Turbo version? These changes are experimental by nature. Rather than folding unproven adjustments into the mainline release, Catalyst exists as a separate track so the standard release stays stable while this build gets real-world testing. Think of it as the skunkworks branch.


⚙️ Personal Settings (Forge Neo)

Required Additional Files

Make sure you also have the following:
16 GB+ VRAM: qwen3_4b.safetensors
8–12 GB VRAM: qwen34bfp8_scaled.safetensors
All VRAM sizes VAE: ae.safetensors


This model is shared as-is, for users who enjoy experimenting, benchmarking, and pushing models outside the comfort zone.

Feedback, findings, and edge cases are welcome - this release exists primarily to learn from real-world usage.