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Z Image Turbo Image to Image: Fast Photoreal Image Editing on Playground and API | RunComfy

tongyi-mai/z-image/turbo/image-to-image

Transform images into photorealistic visuals with fast, high-fidelity generation, bilingual support, and precision lighting control optimized for creative design and production speed.

URL of image for Image-to-Image generation.
The number of inference steps to perform.
Whether to enable prompt expansion. Note: this will increase the price by 0.0025 credits per request.
The format of the generated image.
The strength of the image-to-image conditioning.

Introduction to Z Image Turbo Image to Image

Z Image Turbo Image to Image image-to-image is an advanced visual generation tool built on the high-performance Z-Image-Turbo framework from the Alibaba Tongyi-MAI team. Whether you're working on design prototypes, ad visuals, or multilingual creative projects, this tool’s optimized architecture delivers a seamless balance of precision and speed.
Z Image Turbo Image to Image empowers creators, designers, and developers to transform input prompts into lifelike, instruction-following visual results. You can generate realistic products, portraits, or scene compositions in seconds with effortless text clarity and lighting control.

Examples of Z Image Turbo Image to Image

Z Image Turbo Image to Image on X Platform

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Frequently Asked Questions

What is Z Image Turbo Image to Image and what makes it special?

Z Image Turbo Image to Image is a high-performance AI model built for fast and accurate text-based or image-to-image visual generation. It uses a distilled 6-billion parameter S3-DiT architecture that balances speed, bilingual capabilities, and high fidelity across Chinese and English outputs.

How does Z Image Turbo Image to Image handle image-to-image generation?

Z Image Turbo Image to Image performs image-to-image transformation by understanding both visual and textual cues in a single unified stream. This ensures high consistency in style, lighting, and object placement while maintaining sub-second rendering speed on supported GPUs.

Is Z Image Turbo Image to Image free to use?

Z Image Turbo Image to Image offers a free trial with complimentary credits for new users through the Runcomfy playground. After the trial, you will need to spend credits based on the generation policy listed in the platform’s 'Generation' section.

Who should use Z Image Turbo Image to Image?

Z Image Turbo Image to Image is ideal for designers, marketers, photographers, and developers who need fast, high-quality bilingual image-to-image or text-to-image results. It’s especially useful for product visuals, mockups, and multilingual content creation.

What are the technical requirements to run Z Image Turbo Image to Image?

Z Image Turbo Image to Image runs efficiently on GPUs with as little as 16 GB VRAM and supports Apple Silicon via MPS. It’s optimized for enterprise GPUs such as H100/H800, but can also operate smoothly on local or web deployments.

How does Z Image Turbo Image to Image compare to other image-to-image generators?

Z Image Turbo Image to Image differentiates itself with its 8-step inference and S3-DiT backbone, allowing faster image generation and more accurate text rendering than many larger or slower models. It retains top-tier quality while being resource-friendly.

What kind of outputs can I expect from Z Image Turbo Image to Image?

Z Image Turbo Image to Image delivers photorealistic images suitable for portraits, product renders, and complex scene compositions. It’s also capable of embedding bilingual text directly and clearly into the generated imagery.

Where can I access Z Image Turbo Image to Image?

You can access Z Image Turbo Image to Image through the Runcomfy AI playground at runcomfy.com/playground. The tool works well on mobile browsers and supports both logged-in and credit-based usage.

Are there any limitations with Z Image Turbo Image to Image?

While Z Image Turbo Image to Image achieves excellent quality with reduced latency, the output may vary for highly abstract or unusual prompts. The model focuses on realism and prompt fidelity, so extremely stylized or experimental results may require fine-tuning.