Z-Image Turbo + Controlnet (with LoRA fix) + 4k Upscaling + Detail Daemon

❤️ If you enjoy my work and would like to support me, consider buying me a ☕ Coffee . You can find a more simple, faster, GGUF compatible version of this workflow here, in case you need a more basic workflow: ZIT standard workflow This workflow is designed to give you full control over image generation, whether you’re working with ControlNet, LoRAs, and/or upscaling. It uses a dual sampler setup with the RES4LYF pack to fix the quality issues ControlNet has when paired with LoRAs. Main Features Simple generation Standard Z-Image Turbo image generation Fun-ControlNet V2.1 (2026) Supports multiple control conditions (Canny, Depth, Pose, MLSD, HED, Scribble, and Gray). SAM3 segmentation For high-accuracy character/object pose reference isolation. LoRA fix LoRA hooks for variable LoRA strengths during generation. The dual sampling process injects your LoRAs at a low strength during the first steps to guide the model without degrading the image, while the full strength of your LoRAs is applied in the final steps, resulting in a high-quality image with strong character consistency. You get 8 LoRA slots at your disposal. Lora used for this demo: Woman037 by Huslyo123 Detail control Smoothness control and Detail Daemon give you full control over the details in your final image. 4K Upscaler Ultra high-quality upscaling with SeedVR2. Detailed instructions are contained within the workflow itself: - Yellow nodes are input and configuration nodes you can change to suit your needs. - Red nodes are instructions and helpful notes