Run your AI Toolkit-trained Z-Image De-Turbo LoRA in ComfyUI with training-matched behavior using a single RCZimageDeturbo custom node.

Who it's for: creators who want this pipeline in ComfyUI without assembling nodes from scratch. Not for: one-click results with zero tuning — you still choose inputs, prompts, and settings.

Open preloaded workflow on RunComfy

Open preloaded workflow on RunComfy (browser)

Why RunComfy first
- Fewer missing-node surprises — run the graph in a managed environment before you mirror it locally.
- Quick GPU tryout — useful if your local VRAM or install time is the bottleneck.
- Matches the published JSON — the zip follows the same runnable workflow you can open on RunComfy.

When downloading for local ComfyUI makes sense — you want full control over models on disk, batch scripting, or offline runs.

How to use (local ComfyUI)
1. Load inputs (images/video/audio) in the marked loader nodes.
2. Set prompts, resolution, and seeds; start with a short test run.
3. Export from the Save / Write nodes shown in the graph.

Expectations — First run may pull large weights; cloud runs may require a free RunComfy account.

Overview

Bring AI Toolkit-trained Z-Image De-Turbo LoRAs into ComfyUI without the usual preview drift. The workflow centers on RC Z-Image De-Turbo (RCZimageDeturbo), which routes generation through a De-Turbo-specific inference pipeline aligned with AI Toolkit preview sampling. This pipeline-level path keeps LoRA injection consistent and preserves De-Turbo-correct defaults for predictable, repeatable outputs. For the closest training-matched results, mirror your preview resolution, steps, guidance, and seed.

Important nodes:

• SaveImage

Notes

Z-Image De-Turbo LoRA Inference in ComfyUI | RunComfy Workflow (Training-Matched Results) — see RunComfy page for the latest node requirements.