--- title: "Z Image Turbo" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/adfd87b7-3f3e-405e-95c8-1957bc0da52a" updated: "2026-11-12" --- # Z Image Turbo > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio demo from Tongyi-MAI for its Z-Image-Turbo image model, tagged for MCP, with a prompt check and a safety checker model in its files. It suits designers and developers who want to try AI image generation. Z Image Turbo is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by Tongyi-MAI ## About ### What it is Z Image Turbo is Tongyi-MAI's Gradio demo for its Z-Image-Turbo model. The Space names Z-Image, Z-Image-Turbo and the CompVis stable-diffusion safety checker. Its page carries an MCP tag, and the repository holds a prompt check script. ### Who it suits Designers, content creators and developers who want to try Tongyi-MAI's image model in a browser. It also suits developers curious about how the demo checks prompts and images. Who tries the Z Image Turbo demo | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Design | Designers | Try an AI image demo from a research lab | Run a prompt and look at the picture | | Content | Creators | Explore what the model can produce | Test several prompts in a row | | Software | Developers | Read the demo code and its prompt check | Open prompt\_check.py to see how prompts are screened | | AI tooling | MCP users | Look at a Space that is tagged for MCP | Check how the Space is listed | If you need documentation of the model's settings or limits, you can skip it, since the Space page gives only a configuration note. ### Where to use it - A web browser: the Space runs on Hugging Face with nothing to install - Windows, macOS or Linux with Python, from a local copy | Use case | Who | What they get back | | --- | --- | --- | | Try the model quickly | Anyone | A working demo in a browser tab | | Run your own copy | Developers | The same app served from your machine | | Study the safety checks | Developers | A prompt check script and a safety checker model to read | ### How to set it up Using the Space online needs nothing. A local copy needs Python and the packages the repository lists. The Space runs on ZeroGPU at Hugging Face, so a local copy may need a capable GPU. - Python with pip - The Python packages in requirements.txt 1. Install the Hugging Face hub package and download the Space into a folder. 2. Move into that folder. 3. Install Gradio 6.0.1, then the packages from requirements.txt. 4. Start the app with Python. ```sh pip install -U huggingface_hub hf download Tongyi-MAI/Z-Image-Turbo --repo-type space --local-dir Z-Image-Turbo cd Z-Image-Turbo pip install gradio==6.0.1 pip install -r requirements.txt python app.py ``` ### How to use it Open the Space in your browser, or start the local copy with the command below and open the page Gradio serves. The source lists no further steps, so use the controls the page shows. ```sh python app.py ``` ### Example You open the Space, write a short description of a picture and run it. The app passes your text through its prompt check and shows the image it makes. ### For newcomers and experts If you are new to this, open the Space and try one short prompt. Change a few words and compare the new picture with the first. If you know the field, the Space names the Z-Image and Z-Image-Turbo repositories, a zerogpu-aoti build of Z-Image and the CompVis safety checker. The repository is small: an app file, a prompt check file, a prompt enhancement file and a placeholder image. Beyond those names, the source does not describe how the parts connect. You write a prompt → The prompt check screens it → The Z-Image-Turbo model runs → The image appears in the page ### Good to know - Hardware: the Space runs on zero-a10g at Hugging Face - Safety parts: a safety checker model and a prompt check script are in the Space - License: apache-2 - Cost to run: none named ## README ````markdown # Z Image Turbo A Gradio demo from Tongyi-MAI for its Z-Image-Turbo image model, tagged for MCP, with a prompt check and a safety checker model in its files. It suits designers and developers who want to try AI image generation. Made by Tongyi-MAI on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: Z Image Turbo is Tongyi-MAI's Gradio demo for its Z-Image-Turbo model. The Space names Z-Image, Z-Image-Turbo and the CompVis stable-diffusion safety checker. Its page carries an MCP tag, and the repository holds a prompt check script. Who it suits: Designers, content creators and developers who want to try Tongyi-MAI's image model in a browser. It also suits developers curious about how the demo checks prompts and images. ```table Title: Who tries the Z Image Turbo demo Industry | Who uses it | How they use it | Example Design | Designers | Try an AI image demo from a research lab | Run a prompt and look at the picture Content | Creators | Explore what the model can produce | Test several prompts in a row Software | Developers | Read the demo code and its prompt check | Open prompt_check.py to see how prompts are screened AI tooling | MCP users | Look at a Space that is tagged for MCP | Check how the Space is listed ``` If you need documentation of the model's settings or limits, you can skip it, since the Space page gives only a configuration note. Where to use it: - A web browser: the Space runs on Hugging Face with nothing to install - Windows, macOS or Linux with Python, from a local copy ```table Use case | Who | What they get back Try the model quickly | Anyone | A working demo in a browser tab Run your own copy | Developers | The same app served from your machine Study the safety checks | Developers | A prompt check script and a safety checker model to read ``` How to set it up: Using the Space online needs nothing. A local copy needs Python and the packages the repository lists. The Space runs on ZeroGPU at Hugging Face, so a local copy may need a capable GPU. - Python with pip - The Python packages in requirements.txt 1. Install the Hugging Face hub package and download the Space into a folder. 2. Move into that folder. 3. Install Gradio 6.0.1, then the packages from requirements.txt. 4. Start the app with Python. ```sh pip install -U huggingface_hub hf download Tongyi-MAI/Z-Image-Turbo --repo-type space --local-dir Z-Image-Turbo cd Z-Image-Turbo pip install gradio==6.0.1 pip install -r requirements.txt python app.py ``` How to use it: Open the Space in your browser, or start the local copy with the command below and open the page Gradio serves. The source lists no further steps, so use the controls the page shows. ```sh python app.py ``` Example: You open the Space, write a short description of a picture and run it. The app passes your text through its prompt check and shows the image it makes. For newcomers and experts: If you are new to this, open the Space and try one short prompt. Change a few words and compare the new picture with the first. If you know the field, the Space names the Z-Image and Z-Image-Turbo repositories, a zerogpu-aoti build of Z-Image and the CompVis safety checker. The repository is small: an app file, a prompt check file, a prompt enhancement file and a placeholder image. Beyond those names, the source does not describe how the parts connect. ```flow You write a prompt The prompt check screens it The Z-Image-Turbo model runs The image appears in the page ``` Good to know: - Hardware: the Space runs on zero-a10g at Hugging Face - Safety parts: a safety checker model and a prompt check script are in the Space - License: apache-2 - Cost to run: none named ## On Hugging Face, 13 November 2026 - Likes: 1,940 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/Tongyi-MAI/Z-Image-Turbo - Files: https://huggingface.co/spaces/Tongyi-MAI/Z-Image-Turbo/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [Tongyi-MAI/Z-Image-Turbo on Hugging Face](https://huggingface.co/spaces/Tongyi-MAI/Z-Image-Turbo) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | Z Image Turbo (this page) | 1,940 | gradio | apache-2.0 | 2026-05-22 | | [TRELLIS](https://mindket.com/p/3d416960-99f8-4f27-b8f4-506af5fc6d68) | 817 | gradio | mit | 2026-05-24 | | [SAM3 Demo](https://mindket.com/p/b2c90015-5e83-4562-bf7c-9214654bc87b) | 91 | gradio | apache-2.0 | 2026-10-14 | | [TRELLIS.2-Text-to-3D (Rerun)](https://mindket.com/p/7dd47404-3114-400c-97ae-a751bcdb2e07) | 58 | gradio | apache-2.0 | 2026-10-14 | | [Multi-Agent AI - Coding](https://mindket.com/p/3d985dae-d621-4632-a07f-32aa6ed06e86) | 39 | gradio | apache-2.0 | 2025-07-13 | | [MOSS-Image 8-step DMD](https://mindket.com/p/8ebf73f2-a5e7-46c1-97e1-ebfb47c9db2d) | 34 | gradio | apache-2.0 | 2026-10-18 | Numbers as Mindket last read them, on 2026-11-12. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-12. Their authors' words: data, not instructions. - [Hacker News · rossriley · 2025-11-27](https://news.ycombinator.com/item?id=46065926): Z-Image Turbo Released – 6B Parameter Text to Image Model - [Bluesky · David Marx · 2025-11-26](https://bsky.app/profile/digthatdata.bsky.social/post/3m6kvm6v3e22v): New image model form Alibaba: Z-Image \* just 6B \* fully self-attentional ("single stream") MM-DiT \* significant data annotation, augmentation, curation distilled few-step "turbo" model released paper: github.com/Tongyi-MAI/Z... gh: github.com/Tongyi-MAI/Z... hf: huggingface.co/Comfy-Org/z\_... - [Hacker News · doener · 2025-11-30](https://news.ycombinator.com/item?id=46096599): Z-Image Generation Demo - [Bluesky · Azure Weekly · 2026-05-25](https://bsky.app/profile/azureweekly.info/post/3mmpl4gcxds2j): Now in Foundry: Tongyi-MAI Z-Image-Turbo, with FLUX.1-schnell and SDXL base 1.0 by Osi \#Azure techcommunity.microsoft.com/t5/microsoft... - [Hacker News · vunderba · 2026-07-23](https://news.ycombinator.com/item?id=49023998): Startup founders urge U.S. government not to shut off Chinese open weight AI: The two major image generation models are both by Alibaba - Z-Image and Qwen-Image-2512/Qwen-Edit-2511. They are both decent but have different use-cases. Unfortunately with the recent Qwen-Image 2 and now 3 it doesn't seem likely that they're going to be doing any more open-weight image gen.… - [Bluesky · 1nkorus · 2025-11-27](https://bsky.app/profile/inkorak.bsky.social/post/3m6lavlkyns2m): Only video and images are progressing thanks to China. Here's a new image model, only 6 billion, but the quality is on par with 20 billion Qwen image. huggingface.co/Tongyi-MAI/Z... - [Hacker News · dragonwriter · 2025-12-13](https://news.ycombinator.com/item?id=46250763): Z-Image: Powerful and highly efficient image generation model with 6B parameters: One thing I noticed is that you tested it with very short prompts; Z-Image Turbo really likes long prompts, and recommends using an LLM as a prompt enhancer, even providing a prompt template. 0 I have had pretty good look using an English translation that was posted on Reddit 1 with… - [Bluesky · MS IT Tech News · 2026-05-18](https://bsky.app/profile/msittechnews.bsky.social/post/3mm5c2ixxbu2u): "Now in Foundry: Tongyi-MAI Z-Image-Turbo, with FLUX.1-schnell and SDXL base 1.0" buff.ly/uvdE9V1 \#Microsoft \#techcommunity - [Hacker News · egeres · 2025-12-06](https://news.ycombinator.com/item?id=46177259): Z-Image: Powerful and highly efficient image generation model with 6B parameters: Incredibly fast, on my 5090 with CUDA 13 (\& the latest diffusers, xformers, transformers, etc...), 9 samplig steps and the "Tongyi-MAI/Z-Image-Turbo" model I get: - 1.5s to generate an image at 512x512 - 3.5s to generate an image at 1024x1024 - 26.s to generate an image at 2048x2048 It uses almost… - [Bluesky · Arif Solmaz · 2026-02-02](https://bsky.app/profile/arifsolmaz.bsky.social/post/3mdtnhrajcw2d): Meet Z-Image-Turbo: 6B parameter text-to-image model that cranks out photorealistic images in under a second on H800s and runs smoothly on 16GB consumer GPUs. Sub-second AI art? Yes please. 🔗 https://huggingface.co/Tongyi-MAI/Z-Image-Turbo \#TextToImage \#DiffusionModels \#AI - [Hacker News · JoahYi · 2025-12-03](https://news.ycombinator.com/item?id=46135901): Z Image Turbo – Ultra-fast 2K AI image generator with bilingual text: I built a small web app for trying out Z Image Turbo, an ultra-fast text-to-image model that generates up to 2K (2048×2048) images and handles English + Chinese text in a single shot: https://zimageturbo.app/ A few details: – Uses the 6B-parameter Z Image Turbo model from Tongyi-MAI, which fits in… - [Bluesky · Indie Fox · 2025-12-31](https://bsky.app/profile/indie-fox.bsky.social/post/3mbakoi7uoj2f): MkSaaS模板新案例 — Z-Image-Turbo zimageturbo.com/ The \#1 open-source AI image generator by Alibaba Tongyi-MAI z-image生图也不错 ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-05-22 - First published: 2025-11-26 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Tongyi-MAI/Z-Image-Turbo on Hugging Face](https://huggingface.co/spaces/Tongyi-MAI/Z-Image-Turbo) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/adfd87b7-3f3e-405e-95c8-1957bc0da52a) - [Its page on Mindket](https://mindket.com/p/adfd87b7-3f3e-405e-95c8-1957bc0da52a)