Now fully launched and available for all public community usersMay 2025

Z-Image AI Image Generator

Built by Tongyi-MAI, Z-Image is an open-source 6B image foundation model designed for prompt alignment, flexible visual output, and specialized downstream variants including Turbo and Edit. Run text-to-image and streamlined single-reference image-to-image pipelines directly in your browser using this tool.

Getting Started with Z-Image

Generate top-tier visuals with Z-Image directly on this platform for text-to-image and simplified single-reference image-to-image

Begin with a detailed prompt, upload a single reference image when needed, and polish your results with quick, targeted adjustments while keeping your prompt clear and precisely defined.

Describe the subject and visual goal

Craft a detailed prompt that outlines your core subject, camera angle, lighting setup, composition, and any mandatory text for your finished image.

Upload a Single Reference Image When Required

To lock in a specific mood, product silhouette, or general layout direction, upload a single reference image and guide the generation output with clear, natural language prompts.

Generate Quick Variations and Polish Results

Produce images in your desired aspect ratio, compare multiple generated options, and adjust your prompt until the composition and any included text match your vision perfectly.

Core Strengths of Z-Image

What Makes Z-Image Stand Out as a Top-Tier Base Image Model

Z-Image is an open-source 6B foundation model known for reliable prompt alignment, a robust lineup of variant models, and fully supported local deployment workflows.

Open-Source 6B Foundation Model

Z-Image serves as the foundational base model for the full product family, allowing developers and creators to examine, fine-tune, and deploy the official upstream build without being locked into a closed, hosted-only platform.

The official upstream Apache-2.0 release is fully public and accessible via GitHub and Hugging Face.

It serves as the foundation for downstream family variants such as Z-Image-Turbo and Z-Image-Edit.

Opt for this model when direct access to model weights and local deployment options are your top priorities, rather than only relying on one-click hosted generation.

Precise Prompt and Negative-prompt Control for Clear, Predictable Results

Official documentation highlights robust prompt alignment and effective negative prompt practices, guaranteeing that your prompt adjustments are clearly reflected in the final generated output.

This model performs optimally when you clearly outline your subject, composition, desired style, and elements you wish to exclude from the final image.

This level of control is especially valuable for poster design, product photography, and layout-sensitive prompt projects.

Iterating and comparing generated options is far simpler when the core prompt remains consistent across every generation run.

Single Base Model for Diverse Visual Styles and Use Cases

As the non-distilled base model, Z-Image allows you to transition seamlessly between realistic photography, polished poster layouts, and more stylized creative directions without switching between different model families.

It supports transitions between realistic, poster-style, and fully stylized creative directions without locking you into a single aesthetic too early in your creative workflow.

It’s perfect for testing different subject identities, poses, compositions, and art direction adjustments using the same core prompt base model.

This flexibility is incredibly useful during the initial brainstorming phase, before you settle on a single final creative direction.

Full Local Runtime Support and ComfyUI Integration

Z-Image is already fully compatible with diffusers-based pipelines, local inference tools, ComfyUI utility apps, and community workflow bundles.

Established local inference workflows and community-built tools are already available, rather than only relying on hosted demo versions.

You can seamlessly integrate it with LoRA, ControlNet, and a wide array of custom workflow tests.

This level of support is critical if local deployment is a key factor in your model selection process.

Best use cases

Ideal Use Cases for Z-Image

Designed for prompt-guided image generation, poster layout design, product-centric visuals, and single-reference refinement tasks directly on this platform.

Prompt-Driven Product & Marketing Visuals

Produce sharp product photography, professional packaging mockups, targeted ad concepts, and landing page hero visuals when you require precise framing, consistent material rendering, and polished studio lighting.

Poster & Typography-Focused Creative Concepts

Use Z-Image for event posters, social media graphics, and layout-focused creative projects where precise prompt control and clear, legible text are essential.

Reference-based image refinement

Polish a single reference image to tweak style, framing, or overall visual tone without having to rebuild your core concept from the ground up.

Self-Hosted & Workflow-Focused Deployment

Choose Z-Image if you plan to transition the same model to ComfyUI, local inference runtimes, or a fully customized image generation pipeline down the line.

Effective Prompt Prompt Formulas & Real-World Examples

Writing Effective Z-Image prompts: Real-World Templates and Examples

Each example card highlights a proven prompt prompt pattern, a real-world Z-Image generated output, and the precise writing decisions that fueled its success. Click to expand every card to view the full prompt, breakdown of why it works, and tips for creating your own prompts using these examples as a guide.

Product visual

Leading prompt Alignment Benchmark Standards

Ideal for sharp product visuals with precise commercial lighting control.

A premium skincare bottle photographed on a stone pedestal with soft studio light.

Premium skincare product hero image

Proven industry-standard Prompt best-practice generation workflow guide

[product] + [camera angle] + [surface/background] + [lighting] + [commercial finish]

Dive into Complete prompt Documentation and Technical SpecificationsReveal Full Comprehensive Breakdown

Detailed prompt Breakdown and Overview

A premium glass skincare bottle on a light beige stone pedestal, soft directional studio lighting, subtle shadow, clean editorial composition, luxury e-commerce hero shot, minimal background, realistic reflections, high-end packaging photography.

Core Functional Components That Enable This Prompt To Deliver Standout, High-quality Outputs

This prompt matches Z-Image's strengths in realism, lighting control, and polished commercial visual style.

Desired Final Generated Project Outcome

A clean product image for a landing page, storefront banner, or PDP hero.

Expert Insider Tips for Creative Industry Professionals

Begin by naming your core product, then lock in your preferred shot type and surface configuration for consistent results.
Add specific material terms such as glass, stone, matte, or reflective surfaces to cut down on ambiguity in the generated output.

Poster with text

Leading prompt Alignment Benchmark Standards

Perfect for poster layouts where clear, legible Chinese or English text is a top priority.

A bilingual festival poster with a large Summer Pulse 2026 headline and bold Chinese text.

Bilingual music festival poster

Proven industry-standard Prompt best-practice generation workflow guide

[poster subject] + [headline text] + [text language] + [layout hierarchy] + [background style]

Dive into Complete prompt Documentation and Technical SpecificationsReveal Full Comprehensive Breakdown

Detailed prompt Breakdown and Overview

Modern bilingual music festival poster, bold headline "Summer Pulse 2026", smaller Chinese subtitle "城市电子音乐节", black background with neon orange and cyan accents, clear visual hierarchy, centered headline block, dynamic but readable event poster design.

Core Functional Components That Enable This Prompt To Deliver Standout, High-quality Outputs

Z-Image delivers its strongest results when readable Chinese or English text is integrated into your creative concept, rather than just used as decorative elements.

Desired Final Generated Project Outcome

A text-aware poster concept with a clearer headline block and readable supporting text.

Expert Insider Tips for Creative Industry Professionals

Wrap exact headline text in quotation marks to ensure the model reproduces the wording accurately.
Distinguish your text hierarchy from the overall poster mood and visual style to achieve stronger outcomes.

Image-to-image

Leading prompt Alignment Benchmark Standards

Ideal for single-reference edits where you want to preserve the core object identity fully while making targeted changes.

A matte white skincare pump bottle with sage green accents generated from a reference-driven packaging refresh prompt.

Reference-guided packaging update

Proven industry-standard Prompt best-practice generation workflow guide

[what stays the same] + [what changes] + [new lighting/style/composition direction]

Dive into Complete prompt Documentation and Technical SpecificationsReveal Full Comprehensive Breakdown

Detailed prompt Breakdown and Overview

Keep the bottle shape, cap structure, and front-facing composition from the reference image. Change the packaging style to a modern matte white and sage green palette, softer studio light, cleaner premium skincare branding direction, more refined retail presentation.

Core Functional Components That Enable This Prompt To Deliver Standout, High-quality Outputs

This matches Z-Image's strong single-reference editing capabilities and keeps your request focused.

Desired Final Generated Project Outcome

A controlled refresh that keeps the product identity while upgrading the packaging direction.

Expert Insider Tips for Creative Industry Professionals

Begin by listing the consistent elements you wish to preserve, such as object shape, framing, or core product structure.
Keep your requested changes targeted and precise to ensure a single reference image can guide the generation accurately.

Marketing creative

Leading prompt Alignment Benchmark Standards

Perfect for high-energy commercial ad concepts that require clear product focus and vibrant visuals.

An iced coffee ad visual with splashing cold brew on a sunny beach background.

Fast social ad concept for a coffee brand

Proven industry-standard Prompt best-practice generation workflow guide

[subject] + [visual direction] + [composition] + [color / lighting] + [usage context]

Dive into Complete prompt Documentation and Technical SpecificationsReveal Full Comprehensive Breakdown

Detailed prompt Breakdown and Overview

Commercial iced coffee campaign visual, close-up cold brew cup with ice splash, premium coffee packaging beside the drink, bright summer daylight, beachside mood, energetic composition, crisp product photography, premium beverage advertising style, no logos, no brand names, clean packaging design.

Core Functional Components That Enable This Prompt To Deliver Standout, High-quality Outputs

This prompt clearly lays out product setup, lighting, and campaign objectives while omitting branded copy.

Desired Final Generated Project Outcome

A beverage ad direction you can adapt for paid social, seasonal promos, or a landing page hero.

Expert Insider Tips for Creative Industry Professionals

Mention the marketing channel or intended use context so the composition feels deliberate.
Specify one strong action, such as a splash or close-up, rather than multiple conflicting movements.

When to Pick Z-Image

Pick Z-Image When You Prioritize Open Weights and Local Deployment Flexibility

Opt for Z-Image when you want clear, visible prompt adjustments, plan to reuse the same model beyond this hosted page, or prioritize open model weights and local inference tools.

Select Z-Image When You Want a Single Model You Can Continue Using Down the Line

Choose Z-Image if you want to generate high-quality visuals on this platform first, then continue using the same model family across ComfyUI, local inference runtimes, or fully customized pipelines down the line. This model is an ideal choice when precise prompt control and full model access are your top priorities.

Try Alternative Models When You Prefer Pre-Built Hosted Styles

Try GPT-4o or Seedream if you favor a distinct pre-built visual style and do not prioritize open model weights, local deployment, or downstream customization. These hosted tools typically provide a more simplified, direct generation experience for casual users.

Community Insights & Proof

Community Examples & External Discussions About Z-Image

These curated videos, X posts, and Reddit forum discussions provide real-world external examples and community insights about Z-Image. These resources are most useful as supplementary proof once you’ve grown comfortable with the model and the prompt patterns covered earlier.

Curated Showcase of AI Video Generation Works

Creator-shared community content posts from the X Social Platform

Vibrant Reddit Community Conversation Threads

Open-Source Ecosystem

Relevant Open-Source Projects for Z-Image

These GitHub projects have been manually vetted for direct relevance to Z-Image or the wider model family. Use these resources to examine the model, run it locally, or explore how other developers are building integrations and workflows around it.

GitHub Publicly Available Source Code Repository for the Official Open-Source Project 01

Tongyi-MAI / Z-Image

Official repository

The official upstream Z-Image repository hosted by Tongyi-MAI. This serves as the primary source for the entire 6B model family, official checkpoints, research report links, and standard inference guidance.

10,481 Total number of GitHub stars accrued across the project repository

Apache-2.0

Visit the Official Hub for the Open-Source Project

GitHub Publicly Available Source Code Repository for the Official Open-Source Project 02

Koko-boya / Comfyui-Z-Image-Utilities

ComfyUI utility nodes

A specialized ComfyUI extension built solely for Z-Image image generation workflows, with prompt enhancement, image-aware prompting, and a pre-built integrated sampling node.

116 Total number of GitHub stars accrued across the project repository

Apache-2.0

Visit the Official Hub for the Open-Source Project

GitHub Publicly Available Source Code Repository for the Official Open-Source Project 03

martin-rizzo / AmazingZImageWorkflow

ComfyUI workflow pack

A complete workflow bundle for the Z-Image model family within ComfyUI, including pre-defined creative styles, refiner and upscaler steps, and pre-configured setups for GGUF and Safetensors model checkpoints.

398 Total number of GitHub stars accrued across the project repository

Unlicense

Visit the Official Hub for the Open-Source Project

GitHub Publicly Available Source Code Repository for the Official Open-Source Project 04

martin-rizzo / ComfyUI-ZImagePowerNodes

ComfyUI custom nodes

A curated set of custom ComfyUI nodes built solely for Z-Image and Z-Image-Turbo, including helper tools for style management, latent space setup, and improved workflow ergonomics.

166 Total number of GitHub stars accrued across the project repository

MIT

Visit the Official Hub for the Open-Source Project

FAQs

FAQ

All About Seedance 3 Video and Our Official Platform

What is Z-Image?

Z-Image acts as the foundational base model for the wider Z-Image product family, an open-source 6B image foundation model created by Tongyi-MAI. It prioritizes prompt alignment, versatile visual compatibility, and flexible downstream applications ranging from fine-tuning to local hosting.

What is Z-Image best for?

Z-Image excels at prompt-guided image generation, poster concept design, product-centric visuals, and workflows that you can later transition to ComfyUI, local inference tools, or alternative self-hosted configurations.

Does Z-Image support image-to-image here?

Yes, fully. Inside this platform, Z-Image supports both text-to-image and single-reference image-to-image workflows. Upload a single reference image to lock in core composition, product silhouette, or the overall visual tone of your finished generated content.

Which aspect ratios does Z-Image support here?

Z-Image provides complete support for every major aspect ratio on this platform, including 1:1, 4:3, 3:4, 16:9, and 9:16. This range spans everything from standard square layouts to portrait, landscape, and social media-optimized creative dimensions.

How do I write better prompts for Z-Image?

Begin by mapping out your core subject, then add detailed notes on style, camera angle, lighting conditions, materials, and any mandatory text for your finished image. Z-Image produces its best results when you clearly distinguish non-negotiable elements from flexible variables—this is particularly helpful for poster design, product photography, and single-reference refinement tasks.

When should I use Z-Image instead of GPT-4o or Seedream 4?

Opt for Z-Image when you need an open-source model you can use beyond this hosted platform, particularly if precise prompt control and self-hosting capabilities are your top priorities. Select GPT-4o or Seedream 4 if you mostly want their curated built-in styles and simplified hosted generation workflows.

What is the difference between Z-Image and Z-Image-Turbo?

Z-Image serves as the core 6B foundation model for its product lineup. Z-Image-Turbo is a streamlined, distilled iteration of the base model, tuned for quicker, more lightweight inference. This is why the Turbo variant is a frequent topic of conversation in community workflows and local deployment setups.

Can I use Z-Image images commercially?

The official upstream Z-Image model weights are licensed under Apache-2.0, though commercial usage of any generated assets depends on your unique use case, content guidelines, and this platform’s terms of service. For professional production projects, always follow standard legal and brand approval protocols rather than assuming model outputs are automatically cleared for commercial use.

Is Z-Image open-source and can it be self-hosted?

Yes, fully. Tongyi-MAI published the official upstream Z-Image build, and the model operates natively with diffusers-based pipelines, local inference tools, ComfyUI utility apps, and community workflow bundles. This makes researching, deploying, and adjusting the model significantly simpler than closed, hosted-only AI image generators.

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Related models

Compare Z-Image Against Other Image Models on This Platform

If Z-Image doesn’t align with your specific workflow needs, browse these related model pages to compare prompt generation behavior, visual aesthetics, and targeted use cases.

GPT-4o Image Generator

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Flux 2 Image Generator

Explore Flux 2 for an alternative way to access high-quality polished image generation, featuring a unique prompt generation response and distinct visual style bias.

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Seedream 4 Image Generator

Compare Z-Image against Seedream 4 if you want a more stylized or cinematic visual direction for your creative image outputs.

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Qwen 2 Image Generator

Explore Qwen 2 for another prompt-guided image generation model with reference-based creation and a unique alternative output style.

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Begin Creating with Z-Image Now

Launch the built-in generator, begin with a detailed prompt or a single reference image, and use Z-Image to run controllable text-to-image generation and simplified single-reference edits directly on this platform.

Z-Image AI Image Generator

Writing Effective Z-Image prompts: Real-World Templates and Examples