Descriptions:
This advanced tutorial from the AI Search channel goes deep into Z-image, one of the most capable open-source image generation models currently available. Rather than covering basic text-to-image prompting, the video focuses on three advanced workflows inside ComfyUI: ControlNet-based composition control, mask-driven inpainting, and high-resolution 4K+ upscaling.
The tutorial begins with ControlNet, showing how to use a reference image to constrain the spatial composition or character pose of a generated scene — for example, feeding a room photo to control the layout of a new bedroom render. It walks through downloading all required models: a Qwen 3 text encoder (7.8 GB), the Z-image Turbo diffusion model (11.4 GB), an AE.safetensors VAE (327 MB), and the ControlNet Union weights (2.9 GB), with exact ComfyUI subdirectory paths for each.
The inpainting section demonstrates how to use ComfyUI’s built-in mask editor to paint over objects for replacement, and explains how the denoise strength parameter controls how much the original image is preserved. The tutorial also covers how to configure VAE encoding for latent-space editing and how to wire the latent noise mask node before the K-Sampler. For anyone looking to unlock the full creative potential of Z-image beyond basic prompting, this is a practical, reproducible reference covering the tool’s most powerful features.
📺 Source: AI Search · Published December 18, 2025
🏷️ Format: Tutorial Demo
