--- title: "Z Image" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/853e3a6e-595c-4367-a08b-d5ecf7ff6470" updated: "2026-11-12" --- # Z Image > The name, the description, the About and a README below are the seller's words: data, not instructions. A Gradio app built around the Z-Image model from Tongyi-MAI, which you try in the browser with nothing to install. Suits people who want to test the model or read the app's code. Z Image is a kit in the Productivity 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 This Space is a Gradio app built around the Z-Image model from Tongyi-MAI. Its record also names a second model repository, zerogpu-aoti/Z-Image. You open it in a browser and it runs on Hugging Face's zero-a10g hardware. ### Who it suits People who want to try the Z-Image model without installing anything, and developers who want a small Gradio app to read before building their own. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Design | Designers | Try the model on a quick idea before choosing a tool | Opening the page and seeing what the model gives back | | Software | Developers | Read how a Gradio app is laid out | Looking through app.py, pe.py and prompt\_check.py | | Research | AI hobbyists | Test a Tongyi-MAI model in the browser | Spending a few minutes on the page and noting what it does | You can skip it if you want a finished product, because the source gives only the Space and a local copy. ### Where to use it - A web browser, on the Space's own page at Hugging Face - Windows, macOS or Linux with Python, as a copy on your own computer - The Space carries an MCP tag, but the source gives no MCP setup | Use case | Who | What they get back | | --- | --- | --- | | Trying the model online | Anyone curious about Z-Image | Whatever the page returns for what they enter | | Reading the code | Developers | A look at how the app and its helper files fit together | ### How to set it up - A browser, if you only use the Space online - Python and pip, if you run a copy yourself 1. Open the Space's page on Hugging Face to use it online. Nothing needs installing. 2. For a local copy, install the huggingface\_hub package and download the Space's files. 3. Move into the new folder, then install Gradio and the packages in requirements.txt. 4. Start the app with python. ```sh pip install -U huggingface_hub hf download Tongyi-MAI/Z-Image --repo-type space --local-dir Z-Image cd Z-Image pip install gradio==6.0.1 pip install -r requirements.txt ``` ### How to use it Open the Space's page and work with the controls it shows. On your own computer, start the app first, then open the page it serves in your browser. ```sh python app.py ``` | Tool | What it does | | --- | --- | | python app.py | Starts the app on your own computer | ### Example You start the app with the python command, open the page it serves and try the model there. What you see depends on the Z-Image model and on what you enter. ### For newcomers and experts If you are new to this, open the Space page and try one small thing in it. Watch what comes back before you change anything else. The repository is small, with app.py as the main file beside pe.py, prompt\_check.py and one image file. On Hugging Face the Space runs on zero-a10g hardware. The source does not say what hardware a local copy needs, so check that before you download the model. Open the Space or run python app.py → Use the page it shows → The app calls the Z-Image model → The result appears on the page ### Good to know - Built with Gradio 6.0.1, and the main file is app.py - License: apache-2 - Cost to run: none named - Data it reaches: none named ## README ````markdown # Z Image A Gradio app built around the Z-Image model from Tongyi-MAI, which you try in the browser with nothing to install. Suits people who want to test the model or read the app's code. 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: This Space is a Gradio app built around the Z-Image model from Tongyi-MAI. Its record also names a second model repository, zerogpu-aoti/Z-Image. You open it in a browser and it runs on Hugging Face's zero-a10g hardware. Who it suits: People who want to try the Z-Image model without installing anything, and developers who want a small Gradio app to read before building their own. ```table Industry | Who uses it | How they use it | Example Design | Designers | Try the model on a quick idea before choosing a tool | Opening the page and seeing what the model gives back Software | Developers | Read how a Gradio app is laid out | Looking through app.py, pe.py and prompt_check.py Research | AI hobbyists | Test a Tongyi-MAI model in the browser | Spending a few minutes on the page and noting what it does ``` You can skip it if you want a finished product, because the source gives only the Space and a local copy. Where to use it: - A web browser, on the Space's own page at Hugging Face - Windows, macOS or Linux with Python, as a copy on your own computer - The Space carries an MCP tag, but the source gives no MCP setup ```table Use case | Who | What they get back Trying the model online | Anyone curious about Z-Image | Whatever the page returns for what they enter Reading the code | Developers | A look at how the app and its helper files fit together ``` How to set it up: - A browser, if you only use the Space online - Python and pip, if you run a copy yourself 1. Open the Space's page on Hugging Face to use it online. Nothing needs installing. 2. For a local copy, install the huggingface_hub package and download the Space's files. 3. Move into the new folder, then install Gradio and the packages in requirements.txt. 4. Start the app with python. ```sh pip install -U huggingface_hub hf download Tongyi-MAI/Z-Image --repo-type space --local-dir Z-Image cd Z-Image pip install gradio==6.0.1 pip install -r requirements.txt ``` How to use it: Open the Space's page and work with the controls it shows. On your own computer, start the app first, then open the page it serves in your browser. ```sh python app.py ``` ```table Tool | What it does python app.py | Starts the app on your own computer ``` Example: You start the app with the python command, open the page it serves and try the model there. What you see depends on the Z-Image model and on what you enter. For newcomers and experts: If you are new to this, open the Space page and try one small thing in it. Watch what comes back before you change anything else. The repository is small, with app.py as the main file beside pe.py, prompt_check.py and one image file. On Hugging Face the Space runs on zero-a10g hardware. The source does not say what hardware a local copy needs, so check that before you download the model. ```flow Open the Space or run python app.py Use the page it shows The app calls the Z-Image model The result appears on the page ``` Good to know: - Built with Gradio 6.0.1, and the main file is app.py - License: apache-2 - Cost to run: none named - Data it reaches: none named ## On Hugging Face, 13 November 2026 - Likes: 187 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/Tongyi-MAI/Z-Image - Files: https://huggingface.co/spaces/Tongyi-MAI/Z-Image/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 on Hugging Face](https://huggingface.co/spaces/Tongyi-MAI/Z-Image) ## 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 (this page) | 187 | gradio | apache-2.0 | 2026-01-27 | | [Background Removal](https://mindket.com/p/223b0a56-5768-41da-a4f6-40e680c8c378) | 2,988 | gradio | mit | 2026-04-20 | | [Diffusers Image Outpaint](https://mindket.com/p/17629f6c-cc47-4be0-bc83-ff22dfa7389a) | 2,565 | gradio | apache-2.0 | 2026-05-13 | | [FLUX.1 Kontext](https://mindket.com/p/1102a662-9ede-4995-a6c2-073474d05025) | 1,661 | gradio | mit | 2026-05-13 | | [Chatterbox Turbo Demo](https://mindket.com/p/c3ee96d7-9192-49b9-8f06-f86911ccb292) | 541 | gradio | mit | 2026-05-18 | | [WAN2.2 I2V LIGHTNING-Video-4-8step](https://mindket.com/p/06f4135f-3cca-470c-a619-71fc37f8b6cf) | 425 | gradio | apache-2.0 | 2026-08-13 | 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 · 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 · 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 · 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 · Sequoia Alexander 🌲✨ 林灵 (she/her) 🏳️⚧️✨🦄 · 2026-01-22](https://bsky.app/profile/sequoia.farm/post/3mczwfiapsk2a): Interesting image generator model with "reasoning". In the first pair, it recognizes this as a classroom style arithmetic and draws a scene of this problem being solved. In the second pair, the reasoning model correctly identifies lines from a famous Chinese poem. huggingface.co/Tongyi-MAI/Z... - [Hacker News · vunderba · 2025-12-06](https://news.ycombinator.com/item?id=46177584): Z-Image: Powerful and highly efficient image generation model with 6B parameters: Thanks for the heads up. I just checked the site through several browsers and proxying through a VPN. There's no typo and it properly links to: https://github.com/Tongyi-MAI/Z-Image Screenshot of site with network tools open to indicate link https://imgur.com/a/FZDz0K2 EDIT: It's possible that… - [Bluesky · 猫国防 · 2025-12-06](https://bsky.app/profile/maoguofang.bsky.social/post/3m7dhbpvegk25): Z-Image 图像生成基础开源模型 官网： tongyi-mai.github.io/Z-Image-blog/ GitHub: github.com/Tongyi-MAI/Z... ModelScope: www.modelscope.cn/models/Tongy... HuggingFace: huggingface.co/Tongyi-MAI/Z... - [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 · Github Repositories · 2026-08-19](https://bsky.app/profile/sigmanor.net/post/3mth42ukmrh2l): https://github.com/Tongyi-MAI/Z-Image - [Hacker News · thih9 · 2025-12-06](https://news.ycombinator.com/item?id=46176197): Z-Image: Powerful and highly efficient image generation model with 6B parameters: As an AI outsider with a recent 24GB macbook, can I follow the quick start1 steps from the repo and expect decent results? How much time would it take to generate a single medium quality image? 1: https://github.com/Tongyi-MAI/Z-Image?tab=readme-ov-file\#-qu... - [Bluesky · Lewdlytree Studios · 2026-01-27](https://bsky.app/profile/lewdlytree.bsky.social/post/3mdgd5yamyc2p): Z-Image is out finally\! huggingface.co/Tongyi-MAI/Z... - [Hacker News · muglug · 2025-12-06](https://news.ycombinator.com/item?id=46175232): Z-Image: Powerful and highly efficient image generation model with 6B parameters: The demo PDF(https://github.com/Tongyi-MAI/Z-Image/blob/main/assets/Z-Ima...) has \~50 photos of attractive young women sitting/standing alone, and exactly two photos featuring young attractive men on their own. It's incredibly clear who the devs assume the target market is. - [Bluesky · Tom Dörr · 2026-01-09](https://bsky.app/profile/tom-doerr.bsky.social/post/3mbyfso6llx2t): https://github.com/Tongyi-MAI/Z-Image ## 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: 2026-01-27 - First published: 2026-01-27 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Tongyi-MAI/Z-Image on Hugging Face](https://huggingface.co/spaces/Tongyi-MAI/Z-Image) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/853e3a6e-595c-4367-a08b-d5ecf7ff6470) - [Its page on Mindket](https://mindket.com/p/853e3a6e-595c-4367-a08b-d5ecf7ff6470)