Tongyi-MAI/Z-Image
An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer
Image Generation

Z-Image is the foundation model of the โก๏ธ- Image family, engineered for good quality, robust generative diversity, broad stylistic coverage, and precise prompt adherence. While Z-Image-Turbo is built for speed, Z-Image is a full-capacity, undistilled transformer designed to be the backbone for creators, researchers, and developers who require the highest level of creative freedom.
๐ Key Features
- Undistilled Foundation: As a non-distilled base model, Z-Image preserves the complete training signal. It supports full Classifier-Free Guidance (CFG), providing the precision required for complex prompt engineering and professional workflows.
- Aesthetic Versatility: Z-Image masters a vast spectrum of visual languagesโfrom hyper-realistic photography and cinematic digital art to intricate anime and stylized illustrations. It is the ideal engine for scenarios requiring rich, multi-dimensional expression.
- Enhanced Output Diversity: Built for exploration, Z-Image delivers significantly higher variability in composition, facial identity, and lighting across different seeds, ensuring that multi-person scenes remain distinct and dynamic.
- Built for Development: The ideal starting point for the community. Its non-distilled nature makes it a good base for LoRA training, structural conditioning (ControlNet) and semantic conditioning.
- Robust Negative Control: Responds with high fidelity to negative prompting, allowing users to reliably suppress artifacts and adjust compositions.
๐ Z-Image vs Z-Image-Turbo
| Aspect | Z-Image | Z-Image-Turbo |
|---|---|---|
| CFG | โ | โ |
| Steps | 28~50 | 8 |
| Fintunablity | โ | โ |
| Negative Prompting | โ | โ |
| Diversity | High | Low |
| Visual Quality | High | Very High |
| RL | โ | โ |
๐
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