About Z-Image Turbo

Welcome to the Z-Image project. This is your central hub for everything related to the Z-Image model and its core technologies. We are pleased to introduce Z-Image, an efficient 6-billion-parameter foundation model for image generation. Through systematic optimization, it proves that top-tier performance is achievable without relying on enormous model sizes, delivering strong results in photorealistic generation and bilingual text rendering that are comparable to leading commercial models.

What is Z-Image Turbo?

Z-Image Turbo is a specialized model built on the Z-Image foundation, designed specifically for efficient image generation. At just 6 billion parameters, the model produces photorealistic images on par with those from models an order of magnitude larger. It can run smoothly on consumer-grade graphics cards with less than 16GB of VRAM, making advanced image generation technology accessible to a wider audience.

Z-Image Turbo is a distilled version of Z-Image with strong capabilities in photorealistic image generation, accurate rendering of both Chinese and English text, and robust adherence to bilingual instructions. It achieves performance comparable to or exceeding leading competitors with only 8 steps, making it one of the most efficient image generation models available today.

The Z-Image Model Family

We are publicly releasing two specialized models built on Z-Image:

Key Features

• Efficient 6-Billion Parameter Design: Achieves top-tier performance without massive model sizes
• Photorealistic Generation: Produces images comparable to leading commercial models
• Bilingual Text Rendering: Accurately renders both Chinese and English text within images
• Fast 8-Step Generation: Achieves high-quality results with only 8 inference steps
• Consumer Hardware Compatible: Runs on GPUs with less than 16GB VRAM
• Single-Stream Diffusion Transformer: Efficient architecture for optimal performance
• Open Source: Model code, weights, and online demo are publicly available

Our Mission

With this release, we aim to promote the development of generative models that are accessible, low-cost, and high-performance. By making the model code and weights publicly available, we encourage community exploration and use. We believe that advanced image generation technology should be available to everyone, not just those with access to expensive infrastructure.

Technical Innovation

Z-Image Turbo demonstrates that careful optimization and systematic design can achieve results comparable to much larger models. The single-stream diffusion transformer architecture processes information efficiently, reducing computational overhead while maintaining high-quality output. This approach represents a shift in thinking about model design, prioritizing efficiency and accessibility alongside performance.

How to Use Z-Image Turbo

1. Try the Online Demo: Visit our demo page for instant access with no installation required
2. Use HuggingFace: Access the model through HuggingFace for API integration
3. ModelScope Platform: Available on ModelScope for easy access in China
4. Local Installation: Download and run the model locally for full control and offline usage

Community and Development

The Z-Image project is committed to open development and community engagement. The GitHub repository contains source code, documentation, and examples to help you get started. Users can report issues, suggest features, and contribute improvements through the standard GitHub workflow. We encourage researchers, developers, and creators to explore the technology, build upon it, and share their experiences with the community.

Resources

• GitHub Repository: github.com/Tongyi-MAI/Z-Image
• HuggingFace Model: huggingface.co/Tongyi-MAI/Z-Image-Turbo
• ModelScope: modelscope.cn/models/Tongyi-MAI/Z-Image-Turbo
• Official Homepage: tongyi-mai.github.io/Z-Image-homepage/