Provider Overview

Z-Image Image Generator

Z-Image gives you a focused AI image generation lineup for fast iteration, clean detail, and flexible visual styles. Explore the available models below and start creating on skills.video.

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Z-Image

Z-Image's Feature Offerings

Common strengths surfaced across this provider's most relevant model families.

High-Quality Creative GenerationStrong Diversity And ControllabilityWide Style Range And Negative PromptingFlexible Resolution And Sampling Controls

Z-Image

High-Quality Creative Generation

The official repository describes Z-Image as the foundation model behind Z-Image-Turbo, focused on high-quality generation and stronger aesthetic output. It is positioned for creators and developers who need a more capable base model for image synthesis rather than only the fastest distilled path.

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Z-Image

Strong Diversity And Controllability

The README explicitly states that Z-Image focuses on strong diversity and controllability. It highlights diversity across identities, poses, compositions, and layouts, which makes the model more suitable for iterative creative exploration and downstream customization.

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Z-Image

Wide Style Range And Negative Prompting

The official repo says Z-Image supports a wide range of artistic styles and effective negative prompting. In the recommended parameters for the base model, negative prompts are described as strongly recommended for better control when removing unwanted content or tightening the composition.

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Z-Image

Flexible Resolution And Sampling Controls

For the base Z-Image model, the repository recommends resolutions from 512×512 up to 2048×2048 in total pixel area at any aspect ratio. It also recommends guidance scale 3.0 to 5.0, inference steps 28 to 50, and using cfg_normalization false for general stylism or true for realism.

How to Use Z-Image on skills.video

Choose a Z-Image model

Pick the model family that matches your workflow, then jump into its dedicated model page.

Review examples and features

Check each model's prompt examples, controls, and feature details before generating.

Start creating

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Image Models

Compare Z-Image image models for text-to-image and image editing workflows.

1 models

Z-Image

Z-Image image generation model

FAQs

Common questions about Z-Image models and workflows.

What is Z-Image?

Z-Image is the foundation generation model in Tongyi-MAI's Z-Image family. The official repository describes it as a 6B-parameter image generation model focused on high-quality output, richer aesthetics, diversity, and controllability.

How is Z-Image different from Z-Image-Turbo?

According to the repository, Z-Image is the higher-step foundation model, while Z-Image-Turbo is the distilled fast variant. Z-Image-Turbo targets very low-latency generation, whereas Z-Image is positioned more for higher-quality generation, creative development, and fine-tuning.

What resolutions does Z-Image support?

The official recommended range for the base Z-Image model is 512×512 to 2048×2048 total pixel area, with any aspect ratio.

What generation settings are recommended for Z-Image?

The repository recommends guidance scale 3.0 to 5.0, inference steps 28 to 50, and strongly recommends negative prompts for better control. It also notes that cfg_normalization false is suited to general stylism, while true is better for realism.

Does Z-Image support negative prompts?

Yes. The official README explicitly says negative prompts are strongly recommended for the base Z-Image model when you want better control over unwanted content.

What architecture does Z-Image use?

The project states that Z-Image uses a Scalable Single-Stream DiT (S3-DiT) architecture that combines text, visual semantic tokens, and image VAE tokens into one unified input stream.