--- title: "UGI Leaderboard" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/85570e8b-1c6f-4d8a-bede-5aac8be604d5" updated: "2026-11-12" --- # UGI Leaderboard > The name, the description, the About and a README below are the seller's words: data, not instructions. Shows a leaderboard of AI models scored on what its title calls Uncensored General Intelligence, as a page that runs in the browser or in Docker. For people comparing models. UGI Leaderboard is a kit in the Research 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 DontPlanToEnd ## About ### What it is UGI Leaderboard is a web page that ranks AI models under the title Uncensored General Intelligence Leaderboard. Its data sits in CSV files inside the repository. You can open it online or build and run your own copy with Docker. ### Who it suits It suits people who compare AI models and want a ranking to check before choosing one to try. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | AI research | Researchers | Look up how models compare on this leaderboard | Open the page and find a model you follow | | Software | Developers | Narrow down which models to test | Compare a few models you are considering | | Hobbyist AI | Enthusiasts | Keep track of new models | Return to the page to see what changed | | Data work | Analysts | Read the raw numbers behind the page | Open the CSV files in the repository | Skip it if you need to know how the scores are made, since the source does not explain the method. ### Where to use it - A web browser, on the Space's page at Hugging Face - Docker on your own Windows, macOS or Linux computer | Use case | Who | What they get back | | --- | --- | --- | | Check a model's standing | Researchers | Its place on the leaderboard | | Shortlist models | Developers | A ranked view to start from | | Read the data | Analysts | The leaderboard's CSV files | ### How to set it up The online page needs nothing. A local copy needs Docker, and Python with pip to fetch the files. - Docker - Python and pip, to fetch the files - Windows, macOS or Linux 1. Install the Hugging Face hub library. 2. Download the Space's files into a folder named UGI-Leaderboard. 3. Move into that folder. 4. Build the Docker image. 5. Run the container with port 8050 published, then open that port in your browser. ```sh pip install -U huggingface_hub hf download DontPlanToEnd/UGI-Leaderboard --repo-type space --local-dir UGI-Leaderboard cd UGI-Leaderboard docker build -t ugi-leaderboard . docker run -it -p 8050:8050 ugi-leaderboard ``` ### How to use it Open the Space's page, or start the container with the last command above and browse to port 8050 on your machine. Then look through the leaderboard. ```sh docker run -it -p 8050:8050 ugi-leaderboard ``` ### Example You open the page and look for a model you are thinking of trying. You compare where it sits against the others on the leaderboard before deciding. ### For newcomers and experts Open the online page and scroll through it. That is all you need to do, and nothing has to be installed. The app is built with Docker, serves on port 8050, and has app.py as its main file. The Hugging Face copy runs on the cpu-basic tier. The repository holds two CSV data files, one of them named as an old leaderboard, along with ideologies.js, an Images folder and an assets folder. The record gives no README text, so the scoring method is something you would read in the code and data. Docker builds the image → The container runs app.py → The page is served on port 8050 → You browse the leaderboard ### Good to know - Hardware: The Hugging Face copy runs on the cpu-basic tier. - Gaps: The source has no README text, so the scoring method and columns are not described here. - License: apache-2. - Cost to run: none named. - Data it reaches: The CSV files in the repository. A local run also builds a Docker image and installs the packages in requirements.txt. ## README ````markdown # UGI Leaderboard Shows a leaderboard of AI models scored on what its title calls Uncensored General Intelligence, as a page that runs in the browser or in Docker. For people comparing models. Made by DontPlanToEnd 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: UGI Leaderboard is a web page that ranks AI models under the title Uncensored General Intelligence Leaderboard. Its data sits in CSV files inside the repository. You can open it online or build and run your own copy with Docker. Who it suits: It suits people who compare AI models and want a ranking to check before choosing one to try. ```table Industry | Who uses it | How they use it | Example AI research | Researchers | Look up how models compare on this leaderboard | Open the page and find a model you follow Software | Developers | Narrow down which models to test | Compare a few models you are considering Hobbyist AI | Enthusiasts | Keep track of new models | Return to the page to see what changed Data work | Analysts | Read the raw numbers behind the page | Open the CSV files in the repository ``` Skip it if you need to know how the scores are made, since the source does not explain the method. Where to use it: - A web browser, on the Space's page at Hugging Face - Docker on your own Windows, macOS or Linux computer ```table Use case | Who | What they get back Check a model's standing | Researchers | Its place on the leaderboard Shortlist models | Developers | A ranked view to start from Read the data | Analysts | The leaderboard's CSV files ``` How to set it up: The online page needs nothing. A local copy needs Docker, and Python with pip to fetch the files. - Docker - Python and pip, to fetch the files - Windows, macOS or Linux 1. Install the Hugging Face hub library. 2. Download the Space's files into a folder named UGI-Leaderboard. 3. Move into that folder. 4. Build the Docker image. 5. Run the container with port 8050 published, then open that port in your browser. ```sh pip install -U huggingface_hub hf download DontPlanToEnd/UGI-Leaderboard --repo-type space --local-dir UGI-Leaderboard cd UGI-Leaderboard docker build -t ugi-leaderboard . docker run -it -p 8050:8050 ugi-leaderboard ``` How to use it: Open the Space's page, or start the container with the last command above and browse to port 8050 on your machine. Then look through the leaderboard. ```sh docker run -it -p 8050:8050 ugi-leaderboard ``` Example: You open the page and look for a model you are thinking of trying. You compare where it sits against the others on the leaderboard before deciding. For newcomers and experts: Open the online page and scroll through it. That is all you need to do, and nothing has to be installed. The app is built with Docker, serves on port 8050, and has app.py as its main file. The Hugging Face copy runs on the cpu-basic tier. The repository holds two CSV data files, one of them named as an old leaderboard, along with ideologies.js, an Images folder and an assets folder. The record gives no README text, so the scoring method is something you would read in the code and data. ```flow Docker builds the image The container runs app.py The page is served on port 8050 You browse the leaderboard ``` Good to know: - Hardware: The Hugging Face copy runs on the cpu-basic tier. - Gaps: The source has no README text, so the scoring method and columns are not described here. - License: apache-2. - Cost to run: none named. - Data it reaches: The CSV files in the repository. A local run also builds a Docker image and installs the packages in requirements.txt. ## On Hugging Face, 13 November 2026 - Likes: 2,199 - Built with: docker - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/DontPlanToEnd/UGI-Leaderboard - Files: https://huggingface.co/spaces/DontPlanToEnd/UGI-Leaderboard/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 [DontPlanToEnd/UGI-Leaderboard on Hugging Face](https://huggingface.co/spaces/DontPlanToEnd/UGI-Leaderboard) ## 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 | | --- | --- | --- | --- | --- | | UGI Leaderboard (this page) | 2,199 | docker | apache-2.0 | 2026-10-17 | | [Open LLM Leaderboard](https://mindket.com/p/f179f58f-4514-4b60-b61f-b86395bec554) | 14,156 | docker | apache-2.0 | 2026-05-27 | | [MTEB Leaderboard](https://mindket.com/p/7a22b461-ef19-4980-ac74-6651115182dd) | 7,773 | docker | mit | 2026-11-12 | | [CADGenBench Leaderboard](https://mindket.com/p/a743858b-b306-499b-8861-02d2800f2892) | 90 | docker | apache-2.0 | 2026-08-07 | | [Microduck Sandbox](https://mindket.com/p/3ee8f9e8-61ad-4382-b1f0-74011211142f) | 804 | docker | apache-2.0 | 2026-11-06 | | [Visualize Dataset (v2.0+ latest dataset format)](https://mindket.com/p/a41cd404-e729-4615-9dc9-3d957f6bb38e) | 754 | docker | apache-2.0 | 2026-11-10 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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 · spiritual · 2026-01-16](https://news.ycombinator.com/item?id=46641488): Uncensored General Intelligence (UGI) Leaderboard - [Bluesky · Brian Campbell · 2026-05-02](https://bsky.app/profile/unlambda.hachyderm.io.ap.brid.gy/post/3mkvb5uunrdc2): @liztai There's a nice leaderboard here that helps you rank models based on how censored they are, how smart they are, political leanings, etc: https://huggingface.co/spaces/DontPlanToEnd/UGI-Leaderboard You can set it up to filter models based on your preferences. One thing you'll find is … - [Hacker News · lukewarm707 · 2026-07-29](https://news.ycombinator.com/item?id=49095021): Kimi Linear: An Expressive, Efficient Attention Architecture (2025): "Uncensored General Intelligence" is a very good and well maintained leaderboard: https://huggingface.co/spaces/DontPlanToEnd/UGI-Leaderboard the stock cn models do have refusals, although fewer than us models. critically the cn models are mostly open weights, many in the top 10 UGI are uncensored… - [Bluesky · HN · 2026-01-16](https://bsky.app/profile/hnws.bsky.social/post/3mciuengnhd2j): Uncensored General Intelligence (UGI) Leaderboard L: https://huggingface.co/spaces/DontPlanToEnd/UGI-Leaderboard C: https://news.ycombinator.com/item?id=46641488 posted on 2026.01.15 at 19:30:22 (c=0, p=4) - [Hacker News · nabakin · 2026-04-02](https://news.ycombinator.com/item?id=47619074): Google releases Gemma 4 open models: I know Arc AGI 2 has a private test set and they have a good amount of results0 but it's not a conventional benchmark. Looking around, SWE Rebench seems to have decent protection against training data leaks1. Kagi has one that is fully private2. One on HuggingFace that claims to be fully… - [Hacker News · kouteiheika · 2026-02-03](https://news.ycombinator.com/item?id=46874895): X offices raided in France as UK opens fresh investigation into Grok: This is really amusing to watch, because everything that Grok is accused of is something which you can also trigger in currently available open-weight models (if you know what you're doing). There's nothing special about Grok in this regard. It wasn't trained to be a MechaHitler, nor to generate… - [Hacker News · redman25 · 2025-12-26](https://news.ycombinator.com/item?id=46389219): MiniMax M2.1: Built for Real-World Complex Tasks, Multi-Language Programming: https://www.swebench.com https://swe-rebench.com https://livebench.ai/\#/ https://eqbench.com/\# https://contextarena.ai/?needles=8 https://metr.org/blog/2025-03-19-measuring-ai-ability-to-com... https://artificialanalysis.ai/leaderboards/models https://gorilla.cs.berkeley.edu/leaderboard.html… - [Hacker News · kouteiheika · 2025-08-01](https://news.ycombinator.com/item?id=44754623): LLM leaderboard – Comparing models from OpenAI, Google, DeepSeek and others: It's not perfect, but, yes: https://huggingface.co/spaces/DontPlanToEnd/UGI-Leaderboard - [Hacker News · swah · 2025-05-15](https://news.ycombinator.com/item?id=43998670): Ask HN: AI Model for Adult Chat?: Check this resource https://huggingface.co/spaces/DontPlanToEnd/UGI-Leaderboard - [Hacker News · jaimex2 · 2024-08-21](https://news.ycombinator.com/item?id=41305601): dead: Likely using one of these: https://huggingface.co/spaces/DontPlanToEnd/UGI-Leaderboard ## 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: 2026-10-17 - First published: 2024-03-13 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open DontPlanToEnd/UGI-Leaderboard on Hugging Face](https://huggingface.co/spaces/DontPlanToEnd/UGI-Leaderboard) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/85570e8b-1c6f-4d8a-bede-5aac8be604d5) - [Its page on Mindket](https://mindket.com/p/85570e8b-1c6f-4d8a-bede-5aac8be604d5)