--- title: "Open Chinese LLM Leaderboard" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/ab469411-9c75-4863-ba31-6485ba337471" updated: "2026-11-12" --- # Open Chinese LLM Leaderboard > The name, the description, the About and a README below are the seller's words: data, not instructions. A leaderboard of large language models for Chinese, run by BAAI as a Gradio Space with datasets for requests and results. For researchers and teams comparing models on Chinese tasks. Open Chinese LLM 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 BAAI ## About ### What it is This Space is a leaderboard of large language models for Chinese, run by BAAI. It lists many open models, from Yi-34B to small community models. Its dataset names, such as requests, results and dynamic\_model\_information, point to a system that tracks evaluation requests and scores. The README is only the Hugging Face configuration pointer. ### Who it suits It suits researchers and engineers choosing a model for Chinese-language work, and model authors who want to see how their model ranks. It also suits developers who want to read how a leaderboard Space is organized. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Research | NLP researchers | Compare open models on Chinese evaluations | Look up where a model sits in the ranking | | Software | ML engineers | Shortlist a model for a Chinese product | Compare a few candidates from the list | | Model authors | Open-model builders | Check how their release ranks | Find their model in the table | | Education | Students | Learn how a leaderboard Space is built | Read app.py and the src folder | Anyone who needs rankings for English-only tasks can skip it, since this board is about Chinese. ### Where to use it The leaderboard runs in two places. - A web browser, on the page of the Space at Hugging Face - Windows, macOS or Linux, as a local copy run with Python | Use case | Who | What they get back | | --- | --- | --- | | Model ranking | Researchers | A table of models with their evaluation results | | Model lookup | Engineers | Where a specific model stands against others | | Code study | Developers | A repository with the app, a dynamic-update script and source folder | ### How to set it up The online page needs nothing installed. A local copy needs the following. - Python and pip - Windows, macOS or Linux - The packages listed in requirements.txt - Access to the datasets the Space names, which hold requests and results 1. Install Python. 2. Install the Hugging Face hub package and download a copy of the Space. 3. Move into the new folder and install Gradio 4.36.1 and the packages in requirements.txt. 4. Start the app with python app.py. ```sh pip install -U huggingface_hub hf download BAAI/open_cn_llm_leaderboard --repo-type space --local-dir open_cn_llm_leaderboard cd open_cn_llm_leaderboard pip install gradio==4.36.1 pip install -r requirements.txt python app.py ``` ### How to use it Open the page and read the leaderboard table. The source does not describe the tabs or filters, so follow what the page shows. On a local copy, this command starts the page. ```sh python app.py ``` | Tool | What it does | | --- | --- | | app.py | Holds the Gradio page | | update\_dynamic.py | A script in the repository for updating model information | | src folder | Holds the app's supporting code | | Results datasets | Hold the scores that the leaderboard shows | ### Example You open the page and look for a model you are considering. The table shows where it ranks among the listed models, so you can compare it with a few others. ### For newcomers and experts If you are new to this, a leaderboard is a table that ranks models by their scores on the same tests. Open the page, find a model you know, and see what it scores. If you know the field, the Space reads several datasets named after open-cn-llm-leaderboard: requests, private-requests, results, private-results and dynamic\_model\_information. It also names a datasets entry from the open-llm-leaderboard project. The repository has a pre-commit config, a Makefile and a pyproject file, and it runs on upgraded CPU hardware. Models are requested for evaluation → Results are stored in datasets → The app reads the datasets → The leaderboard table shows the scores ### Good to know The README holds no description, so the benchmarks and scoring are not documented in the source. Check the page for the tests it reports. - License: Apache 2 - Cost to run: none named - Data it reaches: the leaderboard datasets the Space names - Hardware: upgraded CPU at Hugging Face ## README ````markdown # Open Chinese LLM Leaderboard A leaderboard of large language models for Chinese, run by BAAI as a Gradio Space with datasets for requests and results. For researchers and teams comparing models on Chinese tasks. Made by BAAI 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 leaderboard of large language models for Chinese, run by BAAI. It lists many open models, from Yi-34B to small community models. Its dataset names, such as requests, results and dynamic_model_information, point to a system that tracks evaluation requests and scores. The README is only the Hugging Face configuration pointer. Who it suits: It suits researchers and engineers choosing a model for Chinese-language work, and model authors who want to see how their model ranks. It also suits developers who want to read how a leaderboard Space is organized. ```table Industry | Who uses it | How they use it | Example Research | NLP researchers | Compare open models on Chinese evaluations | Look up where a model sits in the ranking Software | ML engineers | Shortlist a model for a Chinese product | Compare a few candidates from the list Model authors | Open-model builders | Check how their release ranks | Find their model in the table Education | Students | Learn how a leaderboard Space is built | Read app.py and the src folder ``` Anyone who needs rankings for English-only tasks can skip it, since this board is about Chinese. Where to use it: The leaderboard runs in two places. - A web browser, on the page of the Space at Hugging Face - Windows, macOS or Linux, as a local copy run with Python ```table Use case | Who | What they get back Model ranking | Researchers | A table of models with their evaluation results Model lookup | Engineers | Where a specific model stands against others Code study | Developers | A repository with the app, a dynamic-update script and source folder ``` How to set it up: The online page needs nothing installed. A local copy needs the following. - Python and pip - Windows, macOS or Linux - The packages listed in requirements.txt - Access to the datasets the Space names, which hold requests and results 1. Install Python. 2. Install the Hugging Face hub package and download a copy of the Space. 3. Move into the new folder and install Gradio 4.36.1 and the packages in requirements.txt. 4. Start the app with python app.py. ```sh pip install -U huggingface_hub hf download BAAI/open_cn_llm_leaderboard --repo-type space --local-dir open_cn_llm_leaderboard cd open_cn_llm_leaderboard pip install gradio==4.36.1 pip install -r requirements.txt python app.py ``` How to use it: Open the page and read the leaderboard table. The source does not describe the tabs or filters, so follow what the page shows. On a local copy, this command starts the page. ```sh python app.py ``` ```table Tool | What it does app.py | Holds the Gradio page update_dynamic.py | A script in the repository for updating model information src folder | Holds the app's supporting code Results datasets | Hold the scores that the leaderboard shows ``` Example: You open the page and look for a model you are considering. The table shows where it ranks among the listed models, so you can compare it with a few others. For newcomers and experts: If you are new to this, a leaderboard is a table that ranks models by their scores on the same tests. Open the page, find a model you know, and see what it scores. If you know the field, the Space reads several datasets named after open-cn-llm-leaderboard: requests, private-requests, results, private-results and dynamic_model_information. It also names a datasets entry from the open-llm-leaderboard project. The repository has a pre-commit config, a Makefile and a pyproject file, and it runs on upgraded CPU hardware. ```flow Models are requested for evaluation Results are stored in datasets The app reads the datasets The leaderboard table shows the scores ``` Good to know: The README holds no description, so the benchmarks and scoring are not documented in the source. Check the page for the tests it reports. - License: Apache 2 - Cost to run: none named - Data it reaches: the leaderboard datasets the Space names - Hardware: upgraded CPU at Hugging Face ## On Hugging Face, 13 November 2026 - Likes: 128 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/BAAI/open_cn_llm_leaderboard - Files: https://huggingface.co/spaces/BAAI/open_cn_llm_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, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [BAAI/open_cn_llm_leaderboard on Hugging Face](https://huggingface.co/spaces/BAAI/open_cn_llm_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 | | --- | --- | --- | --- | --- | | Open Chinese LLM Leaderboard (this page) | 128 | gradio | apache-2.0 | 2025-07-07 | | [Open VLM Leaderboard](https://mindket.com/p/9382a913-7563-4967-88b1-0f2458cb00bc) | 1,034 | gradio | apache-2.0 | 2026-03-11 | | [Face Swap](https://mindket.com/p/92787455-1f9f-466a-b574-da22b25d6e0a) | 808 | gradio | cc-by-nc-sa-4.0 | 2024-05-22 | | [TTS Spaces Arena](https://mindket.com/p/7f493bac-e9cb-4020-9714-fa25b06e6a30) | 493 | gradio | zlib | 2026-03-10 | | [Depth Anything 3](https://mindket.com/p/c1e531c5-63e1-4315-a529-7fcae3cb7374) | 490 | gradio | cc-by-nc-4.0 | 2025-11-20 | | [BLIP](https://mindket.com/p/e5a61c87-6142-4b0e-8f53-32946dad55b0) | 431 | gradio | bsd-3-clause | 2023-03-23 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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: 2025-07-07 - First published: 2024-01-23 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open BAAI/open_cn_llm_leaderboard on Hugging Face](https://huggingface.co/spaces/BAAI/open_cn_llm_leaderboard) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/ab469411-9c75-4863-ba31-6485ba337471) - [Its page on Mindket](https://mindket.com/p/ab469411-9c75-4863-ba31-6485ba337471)