MODEL PROFILE

Z-Image

Tongyi-MAI · Z-Image

⚡️- Image An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer **Z-Image** is the foundation model of the ⚡️- 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. - **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 languages—from 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.

Image generationlicense:apache-2.0
Context windowNot disclosed
Input → OutputText → Image
Model weightsNot verified
Profile updated2026/10/30 20:28:57
OVERVIEW

Model overview

⚡️- Image An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer **Z-Image** is the foundation model of the ⚡️- 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. - **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 languages—from 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.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

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PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Frequently asked questions

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Sources & traceability

许可证:apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。