z-image-txt2img

# Z-Image Text-to-Image Workflows ## Overview Z-Image is a 6B-parameter image generation model from Alibaba's Tongyi Lab using a Scalable Single-Stream DiT (S3-DiT) architecture. It uses a Qwen text encoder (not CLIP-L/T5), and the same `ae.safetensors` VAE as Flux. Two variants: 1. **Z-Image Base** (and RedCraft finetune) — Full model, supports negative prompts, LoRA training, ControlNet. 10-30 steps. 2. **Z-Image Turbo** — DMD-distilled, 8-10 steps, no effective negative prompts (CFG baked in). ## Models ### RedCraft Redzimage DX1 (Installed — Combined Checkpoint) | Component | Node | Model | Notes | |-----------|------|-------|-------| | **Checkpoint** | `CheckpointLoaderSimple` | `redcraftRedzimageUpdatedJAN30_redzibDX1.safetensors` | 17GB, bundles UNET+CLIP+VAE | RedCraft is a Z-Image Base finetune by the RedCraft team. Designed for faster inference than stock Z-Image Base. Uses `CheckpointLoaderSimple` since it's a combined checkpoint — no need for separate loaders. ### Z-Image Turbo (Separate Components — May Need Download) | Component | Node | Model | Notes | |-----------|------|-------|-------| | **UNET** | `UNETLoader` | `z_image_turbo_bf16.safetensors` | Not currently installed | | **CLIP** | `CLIPLoader` (type=`qwen_image`) | `qwen_3_4b.safetensors` | Not currently installed | | **VAE** | `VAELoader` | `ae.safetensors` | Same as Flux VAE (320MB) | ### Z-Image Base (Separate Components — May Need Download) | Component | Node | Model | Notes | |----------...