Z-Image ComfyUI Workflows

Two things stand out when you reach for Z-Image comfyui workflows: it is fast, and it actually renders text. Z-Image is Alibaba Tongyi Lab's open image-generation family, built on an S3-DiT (Scalable Single-Stream DiT) architecture that feeds text, visual-semantic, and image tokens through one unified stream. Its standout trait is accurate lettering in both English and Chinese, the kind most image models still fumble on posters and infographics. The workflows on this page are the ready-made graphs for running it without wiring the nodes yourself.

The variant most people start with is Z-Image-Turbo, a distilled 6B model that generates in roughly eight sampling steps. That is why it shows up in the quick text-to-image and 2K upscaling workflows here: it iterates fast enough to keep a tight feedback loop, and it stays under about 16GB of VRAM, so a single consumer card can run it. The weights are open on HuggingFace under an Apache 2.0 license, which is what lets you self-host instead of renting generations by the image.

What that means in practice is a model you can lean on for design work, not just pretty pictures. Generate a poster with legible headline text, create social graphics with accurate lettering, run text-to-image at speed, or push a result to a crisp 2K. Because these are open workflows, you control the resolution, the step count, and the variant you load, and you can re-run until the text and composition are right.

Everything here is open and editable. Open a Z-Image workflow on Comfy Cloud with nothing to install, or download it and run it locally if you have a capable GPU. You can swap variants, tune the parameters, and there is no watermark on what you make.