Z Image Base
A stable, versatile, and reliable AI image generation foundation model. Emphasizing stability, structural understanding, and generalization capabilities, ideal for commercial products and secondary development.
AI Image Generator
Technical Specs
Core Technical Parameters
Product Introduction
What is Z Image Base
Z Image Base is an image generation foundation model launched by Alibaba Tongyi Laboratory, using Single-stream Diffusion Transformer (S3-DiT) architecture.
What is Z Image Base
Z Image Base is an image generation foundation model launched by Alibaba Tongyi Laboratory, using Single-stream Diffusion Transformer (S3-DiT) architecture.
Core Capabilities
Five Key Capabilities
- Structural Stability — Human body proportions and object structures remain stable, suitable for scenarios requiring realism and controllability.
- Prompt Understanding — Good understanding of Chinese/English natural language prompts, with reasonable composition based on prompts.
- Generalization — Suitable for various subjects, not picky about types. Can stably generate people, products, scenes, and buildings.
- Commercial Adaptability — Stable and controllable, suitable as the default model for website features, without altering structures randomly.
Version Comparison
Base vs Turbo
Choose the right version for your needs
Base Model — Complete undistilled version, higher quality potential
Retains all training signals and potential; supports variable inference steps (typically higher quality); more flexible combination with LoRA and style fine-tuning; stronger semantic precision; best base for training LoRA and style extensions; suitable for research, fine-tuning, and ultimate quality requirements.
Turbo Model — Distilled optimized version, speed first
Extremely fast inference (typically 8-9 steps); sub-second generation on data center GPUs; smooth output on consumer GPUs (16GB VRAM); suitable for real-time interactive applications; suitable for real-time image generation in products, fast iteration scenarios; balances quality and efficiency.
Fine-tuning/LoRA Development
Base is the preferred base model, retaining complete expressive power
Real-time Applications
Turbo is suitable for web/app real-time generation with sub-second response
Ultimate Quality
Base pursues the highest quality ceiling and detail performance
Limited Resources
Turbo is suitable for 16GB GPU environments, pursuing speed and efficiency
Use Cases
Which Scenarios is it Suitable For
Universal Text-to-Image
Realistic portraits, product display images, interior design renderings, food photography styles, scene concept art
Image-to-Image Structure Preservation
Old photo restoration and style enhancement, line art coloring, sketch to detailed image, mild stylization of real photos
Default Model for Commercial Products
AI avatar generators, product image generation tools, AI poster generation, interior preview
Custom Development
Custom character styles, product-specific templates, corporate brand color custom output styles
LoRA Fine-tuning Base
As a base model for LoRA training, supports custom style and character training
Real-time Generation Applications
Turbo version is suitable for real-time interaction scenarios with sub-second response speed
Base vs LoRA Relationship
Base is a complete foundation model that can be used alone, providing universal generation capabilities; LoRA is a style/feature fine-tuning plugin that needs to be attached to Base to work, changing styles (such as anime, watercolor, Ghibli). The relationship can be understood as: Base = foundation and house structure | LoRA = decoration style package
Advantages & Limitations
Pros & Cons Analysis
Four Key Advantages
Lower Resource Barrier
6B parameter scale, can run on GPUs within 16GB, no need for expensive hardware costs
Open Source License Friendly
Apache 2.0 license, free for commercial use, suitable for self-hosting and privacy compliance
Bilingual Prompt Understanding
Good support for Chinese and English mixed prompts, strong semantic understanding
Architecture Efficiency Leading
Single-stream Diffusion Transformer architecture performs well in efficiency
Three Limitations
Quality Ceiling
Compared to large commercial/closed models (20B+), there is a gap in ultimate artistic feel and detail performance
Inference Speed
Retains complete architecture with more inference steps, not as fast as Turbo distilled version
Ecosystem Maturity
Compared to Stable Diffusion, plugins and community resources are still growing
Competitor Comparison
Comparison with Other Models
| Dimension | Z Image Base | Stable Diffusion XL | Flux.2 |
|---|---|---|---|
| Parameter Scale | 6 B | 20 B+ | 10 B–20 B+ |
| Deployment Difficulty | Lower | Medium | Medium |
| Dev-friendly | ★★★★☆ | ★★★☆☆ | ★★★☆☆ |
| Multi-language Support | ★★★★☆ | ★★★☆☆ | ★★★☆☆ |
| Commercial License Friendly | ★★★★☆ | ★★★☆☆ | Depends on License |
Pricing
Choose the plan that works best for you
Free
Basic features for personal use
- Up to 3 projects
- 1 GB storage
- Basic analytics
- Community support
- Custom domains
- Custom branding
- Lifetime updates
Pro
Advanced features for professionals
- Unlimited projects
- 10 GB storage
- Advanced analytics
- Priority support
- Custom domains
- Custom branding
- Lifetime updates
Lifetime
Premium features with one-time payment
- All Pro features
- 100 GB storage
- Dedicated support
- Enterprise-grade security
- Advanced integrations
- Custom branding
- Lifetime updates
FAQ
Frequently Asked Questions
Ready to Start Using Z Image Base?
Stable, versatile, and product-ready — suitable for most real-world application scenarios