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Z-Image is a 6B parameter image generation model featuring three variants: Z-Image-Turbo (distilled for sub-second inference with 8 NFEs on H800 GPUs), Z-Image-Base (foundation model for fine-tuning), and Z-Image-Edit (specialized for image editing). Built on a Scalable Single-Stream DiT architecture, it excels at photorealistic generation, bilingual text rendering (English/Chinese), and instruction following. The model uses Decoupled-DMD distillation algorithm and DMDR (combining DMD with reinforcement learning) for few-step generation optimization. Available on Hugging Face and ModelScope with PyTorch and Diffusers support.

Tongyi-MAI/Z-Image

🔬 Decoupled-DMD: The Acceleration Magic Behind Z-Image

🤖 DMDR: Fusing DMD with Reinforcement Learning