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CyberRealistic Z-Image Turbo is a build based on the original Z-Image Turbo. It follows the original Z-Image Turbo settings and philosophy, with minimal intervention, exploring how well this setup translates into the CyberRealistic workflow.
⚙️ Personal Settings (Forge Neo)
or
Required Additional Files
Make sure you also have the following:
16 GB+ VRAM: qwen3_4b.safetensors
8–12 GB VRAM: qwen34bfp8_scaled.safetensors (find it on huggingface.co)
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.
Description
Grab this model and many more by joining The Tinkerer on Whop. Membership gets you early releases, private tools and members-only pages, plus a lot more.
👉 Join on Whop
By request: V7.0 INT8 ConvRot version
This version uses INT8 quantization combined with ConvRot. ConvRot applies a rotation before quantization, helping flatten activation/weight outliers and preserve more quality than a straightforward INT8 conversion.
The result is a significantly smaller model with much lower VRAM usage than BF16, while retaining most of the original quality.
Best for:
Low-VRAM systems
GPUs with strong INT8 performance
Anyone wanting a smaller model with minimal quality loss
Current ComfyUI builds support the format natively on NVIDIA Turing and newer GPUs.
Note: INT8 is not automatically faster than FP8. Performance depends on your GPU and backend, so FP8 remains the safer general-purpose choice if you are unsure which version to use.