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Unleash the Power of AI Image Generation with Z-Image-Turbo API

Name: Supercharge Your Applications with the Z-Image-Turbo Image Generation API
Author: Z-Image-Turbo

Seamlessly integrate photorealistic image generation into your applications. Experience sub-second latency and unparalleled quality with our developer-friendly API.

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Runs on 16GB VRAM

Ultra-Fast 8-Step Generation

Bilingual Text Rendering

Key Features for Seamless Integration

Empower your applications with the speed and quality of Z-Image-Turbo.

Ultra-Fast Generation

Generate photorealistic images in just 8 NFEs with sub-second inference latency, even on enterprise H800 GPUs.

Consumer Hardware Compatible

Run professional-grade image generation on consumer devices with 16GB VRAM, democratizing access for all developers.

Bilingual Text Rendering

Accurately render complex text in both English and Chinese, enabling cross-market campaigns and multilingual content creation.

Get Started with the Z-Image-Turbo API in 3 Simple Steps

Easy integration for developers of all levels.

Sign Up & Get API Key

Create your account and obtain your unique API key for secure access.

Integrate the API

Use our comprehensive documentation and code samples to easily integrate the Z-Image-Turbo API into your application.

Generate Images

Send text prompts and receive high-quality, photorealistic images in seconds.

Frequently Asked Questions

Find answers to common questions about the Z-Image-Turbo API.

Z-Image-Turbo, developed by Tongyi-MAI, offers unparalleled speed and efficiency with its 8 NFEs and 6B parameters. It also supports bilingual text rendering and runs comfortably on consumer hardware with 16GB VRAM, unlike models like FLUX.2 or Qwen-Image that require significantly more resources.

The Z-Image-Turbo API supports image resolutions up to 1536x1536, supporting both square and rectangular image formats.

Yes, the Z-Image-Turbo API is suitable for enterprise applications. It has been trained with 314K H800 GPU hours and utilizes the Scalable Single-Stream DiT architecture (S3-DiT) ensuring high-quality, consistent results. Its Decoupled-DMD distillation further enhances performance.

The Z-Image-Turbo utilizes a guidance scale of 0.0. The models are distilled specifically for this configuration to optimize the complex relationship between CFG Augmentation and Distribution Matching within the Decoupled-DMD distillation algorithm.