Model reference · open weights
Z-Image is an open-weight image model from Tongyi-MAI, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
[](https://tongyi-mai.github.io/Z-Image-blog/)  [](https://github.com/Tongyi-MAI/Z-Image)  [](https://huggingface.co/Tongyi-MAI/Z-Image-Turbo)  [](https://huggingface.co/spaces/Tongyi-MAI/Z-Image-Turbo)  [](https://huggingface.co/spaces/akhaliq/Z-Image-Turbo)  [](https://www.modelscope.cn/models/Tongyi-MAI/Z-Image-Turbo)  [](https://www.modelscope.cn/aigc/imageGeneration?tab=advanced&versionId=469191&modelType=Checkpoint&sdVersion=ZIMAGETURBO&modelUrl=modelscope%3A%2F%2FTongyi-MAI%2FZ-Image-Turbo%3Frevision%3Dmaster)  [](assets/Z-Image-Gallery.pdf)  [](https://modelscope.cn/studios/Tongyi-MAI/Z-Image-Gallery/summary)  Welcome to the official repository for the Z-Image（造相）project! ✨ Z-Image Z-Image is a powerful and highly efficient image generation model family with 6B parameters. Currently there are four variants: - 🚀 Z-Image-Turbo – A distilled version of Z-Image that matches or exceeds leading competitors with only 8 NFEs (Number of Function Evaluations). It offers ⚡️sub-second inference latency⚡️ on enterprise-grade H800 GPUs and fits comfortably within 16G VRAM consumer devices. It excels in photorealistic image generation, bilingual text rendering (English & Chinese), and robust instruction adherence. - 🎨 Z-Image – The foundation model behind Z-Image-Turbo. Z-Image focuses on high-quality generation, rich aesthetics, strong diversity, and controllability, well-suited for creative generation, fine-tuning, and downstream development. It supports a wide range of artistic styles, effective negative prompting, and high diversity across identities, poses, compositions, and layouts. - 🧱 Z-Image-Omni-Base – The versatile foundation model capable of both generation and editing tasks. By releasing this checkpoint, we aim to unlock the full potential for community-driven fine-tuning and custom development, providing the most "raw" and diverse starting point for the open-source community. - ✍️ Z-Image-Edit – A variant fine-tuned on Z-Image specifically for image editing tasks. It supports creative image-to-image generation with impressive instruction-following capabilities, allowing for precise edits based on natural langua
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | Tongyi-MAI |
|---|---|
| Type | Image models |
| Parameters (lead) | 6.2B |
| Variants | 1 |
| Runs with | diffusers |
| Released | 2025-11-25 |
| Popularity | 717k downloads / month |
| Likes | 5,178 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| Z-Image-Turbo | 6.2B | BF16 | ~14.2 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys z-image for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (z-image below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/images/generations \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"z-image","prompt":"a red bicycle","size":"1024x1024"}'
Details
Languages
Tags
Papers
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗