Starter
- 100 credits one time purchase
- AI Image Generator & Video Generator
- Seedance 2.5 AI Video Generator
- HD video quality (1080p)
- Commercial use license
- Download enabled
- Email support
Efficient 6B-parameter image generation model with photorealistic quality and bilingual text rendering.

Explore stunning images generated with z-image. Each image showcases the model's photorealistic quality, bilingual text rendering, and efficient generation capabilities.









Z-Image is designed as an efficient foundation model that combines compact architecture with strong visual quality. With Z-Image, you can ship photorealistic generations, bilingual designs, and knowledge-rich imagery without compromising on speed or hardware accessibility.
Z-Image delivers photography-level realism with fine control over lighting, materials, and scene composition. With Z-Image, teams can generate images that feel naturally captured rather than obviously synthetic, while still benefitting from controllable style and structure.
Z-Image achieves ultra-fast inference with only a handful of sampling steps, enabling near real-time creative exploration. On enterprise-grade H800 GPUs, Z-Image can reach sub-second latency so product designers, marketers, and researchers can iterate without waiting.
Z-Image is optimized for bilingual text rendering, handling both Chinese and English text in the same frame. Whether you are composing posters, UI mockups, or content with dense labels, Z-Image maintains legible typography while preserving overall facial realism and scene aesthetics.
Built as a 6B-parameter single-stream diffusion transformer, Z-Image unifies conditional inputs with image latents to maximize efficiency. Z-Image couples Decoupled-DMD distillation with DMDR reinforcement learning so you get top-tier performance without needing massive model sizes.
Explore how Z-Image applies world knowledge, semantic reasoning, and instruction following to different domains. Across product photography, posters, UI concepts, and educational visuals, Z-Image balances fidelity and control so results stay coherent, bilingual, and on brief.
Z-Image specializes in photorealistic generation that can stand beside high-quality photography. With Z-Image, you can control pose, lighting, background, and styling while keeping faces, materials, and scene structure naturally consistent from one prompt to the next.
Z-Image accurately renders both Chinese and English text inside the same layout, from title cards and banners to dense UI mockups. Z-Image keeps typography sharp and legible while still balancing overall composition, facial realism, and visual storytelling.
Trained with rich world knowledge, Z-Image understands cultural references, domains, and scenarios. When you prompt Z-Image with complex concepts or multi-part instructions, the model draws on structured knowledge to keep details grounded instead of hallucinated.
Z-Image uses structured semantic reasoning to understand relationships between objects, layout, and text. This lets Z-Image follow logic and common sense—for example, aligning text with hero objects, placing labels on the right surfaces, and keeping shadows and reflections consistent.
Beyond pure generation, Z-Image can be guided to perform creative editing such as style shifts, background swaps, and targeted transformations. Z-Image responds to precise instructions so you can upgrade campaigns, product shots, and visual narratives without starting from scratch.
Z-Image is tuned for instruction following that respects granular constraints. When you specify colors, camera angles, copy variants, or layout rules, Z-Image treats them as hard requirements, giving teams repeatable behavior for design systems, branding, and multi-language workflows.
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Learn how Z-Image fits into your image generation, editing, and design workflows.
Z-Image is an efficient 6-billion-parameter foundation model for image generation. Z-Image demonstrates that top-tier performance is possible without enormous model sizes, delivering strong photorealistic generation, bilingual text rendering, and practical deployment characteristics.
Z-Image focuses on photorealistic image generation, bilingual text rendering in both English and Chinese, ultra-fast inference with only a few sampling steps, efficient VRAM usage that fits consumer GPUs, rich world knowledge, and creative editing capabilities. With Z-Image, teams can reliably move from text prompts to production-ready visuals.
We offer two specialized models: Z-Image-Turbo for high-speed text-to-image generation and Z-Image-Edit for editing workflows. Z-Image-Turbo is a distilled variant optimized for 8-step inference, while Z-Image-Edit specializes in image-to-image transformations, complex instruction following, and layout-preserving changes.
Z-Image is designed to run smoothly on accessible hardware. Z-Image fits consumer-grade GPUs with less than 16GB of VRAM for everyday experimentation and prototyping. On enterprise-grade H800 GPUs, Z-Image can achieve sub-second inference latency for interactive creative sessions and production services.
Yes. Z-Image is released with model code, weights, and an online demo across GitHub, ModelScope, and HuggingFace. This open distribution allows researchers, practitioners, and product teams to inspect Z-Image, fine-tune it for their own domains, and build tools and workflows on top of the same foundation.
Z-Image adopts a single-stream diffusion transformer architecture that unifies conditional inputs with image latents instead of keeping them separate. Combined with Decoupled-DMD distillation and DMDR reinforcement learning, Z-Image reaches strong performance with a compact 6B configuration, focusing on efficiency, controllability, and bilingual rendering.