Z-Image
Z-Image is an open-source lightweight AI image generation model developed by Alibaba Tongyi Lab, delivering photo-realistic outputs, precise Chinese-English text rendering, and sub-second inference on consumer-grade graphics cards.
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What is Z-Image
Z-Image is a 6B-parameter lightweight AI image generation model launched by Alibaba Tongyi Lab, built on the innovative S³-DiT (Scalable Single-Stream Diffusion Transformer) architecture. As an open-source solution under Apache 2.0 license, it currently has the Z-Image-Turbo distilled high-speed version available for public use, with Z-Image-Base (for customization) and Z-Image-Edit (for image manipulation) to be released soon. Boasting a 24GB weight file and support for 8-step sampling, Z-Image-Turbo enables sub-second inference and can run smoothly on 16GB VRAM consumer GPUs. It topped the Hugging Face trending list on its release day, offering comparable realism and detail to models with over 20B parameters. The model is fully compatible with mainstream ecosystems like Hugging Face and ComfyUI, and also provides API services via Alibaba Cloud ModelStudio for seamless integration into various workflows.
Version Options
Free Version
Deployed using open-source models from Hugging Face, ideal for exploring model capabilities. Service may be unstable due to shared resources, with slower generation speed and basic parameter options only.
Standard Version
Deployed via Alibaba Cloud API, providing stable and reliable generation services. Supports more parameter adjustments, faster generation speed, suitable for production use.
Why Choose Z-Image
Low Hardware Threshold
Runs on 16GB VRAM consumer GPUs (e.g., RTX 4080Ti/4090), eliminating the need for high-end professional hardware and reducing deployment costs
Ultra-Fast Inference
The Turbo version achieves sub-second image generation with just 8 sampling steps, delivering a high-definition image in 2.3 seconds on RTX 4090
Superior Generation Quality
Produces photo-realistic outputs with precise restoration of fine details like hair texture, metal reflections, and fabric folds
Bilingual Text Rendering
Excels at rendering mixed Chinese-English text and complex layouts, solving the common text distortion issue of traditional AI image generators
Strong Semantic Understanding
Built-in prompt enhancer with world knowledge and multicultural understanding, capable of handling complex logical instructions
Open-Source & Customizable
Licensed under Apache 2.0, allowing free commercial use and secondary development with the Base version supporting fine-tuning
Z-Image Application Scenarios
E-Commerce
Generate high-quality product images and detail page posters with accurate bilingual product descriptions to enhance merchandise display
Advertising & Marketing
Batch-produce social media ads and offline banners, balancing visual appeal with clear presentation of promotional copy
Creative Design
Assist artists and designers in creating illustrations, concept art, and design prototypes, exploring diverse artistic styles
Film & Game Development
Generate digital assets such as virtual scenes, character designs, and prop models to accelerate production workflows
Educational Content
Create visual materials like historical scenes and scientific phenomena to improve teaching resource engagement
Design Prototyping
Quickly transform design ideas into visual prototypes, supporting iterative refinement and optimization
How to Use Z-Image
Usage Steps
Environment Preparation
Prepare a GPU with 16GB+ VRAM, install dependencies including PyTorch, Transformers, and the latest version of Diffusers
Obtain Weights
Download Z-Image-Turbo weights from the Hugging Face repository (tongyi-mai/z-image-turbo) or ModelScope platform
Model Inference
Load the model via the Diffusers library, input prompts with customized parameters to generate images, enable Flash Attention for acceleration
Workflow Integration
Import Z-Image-Turbo into ComfyUI and combine with plugins like ControlNet or LoRA for precise image control
API Access
Call Z-Image's API through Alibaba Cloud ModelStudio for cloud-based generation without local deployment
Simple Code Example
Use Python to quickly generate images: load the ZImagePipeline with model weights, input custom prompts, set sampling steps and image size, then generate and save the output. Adjust the random seed to get different results, and refer to official examples for detailed parameter configuration.
Try Z-Image Now
Experience sub-second inference and accurate bilingual text rendering without complex local deployment
Access Z-Image Online GeneratorZ-Image FAQs
Which versions of Z-Image are currently available?
Only Z-Image-Turbo (distilled high-speed version) is open-source and downloadable now. Z-Image-Base (base version) and Z-Image-Edit (editing version) are pending release, with official access channels to be announced later.
What is the minimum hardware requirement for Z-Image?
Z-Image-Turbo runs smoothly on 16GB VRAM GPUs, and is also compatible with lower-spec consumer GPUs like RTX 3060 (6GB VRAM) with minor speed reductions, catering to users with different hardware conditions.
Are there limitations to Z-Image's text rendering capability?
Z-Image handles regular Chinese-English text and complex layouts accurately, but may have flaws in extreme scenarios like artistic fonts or special typography. Post-processing with professional design tools is recommended for such cases.
Does Z-Image support image-to-image and image editing functions?
The current Turbo version focuses on text-to-image generation. Dedicated image-to-image and editing features will be provided by the upcoming Z-Image-Edit, which can modify backgrounds, poses, and text while maintaining identity and lighting consistency.
What is Z-Image's open-source license, and can it be used for commercial purposes?
Z-Image adopts the Apache 2.0 open-source license, allowing commercial use and secondary development. Developers can fine-tune the Base version for customization, provided they comply with relevant open-source agreements.