LVBench Leaderboard

LVBench Leaderboard

The leaderboard page for the LVBench benchmark from zai-org, run as a Gradio app that names the LVBench dataset. For researchers who want to see how models score on it.

Made by zai-org 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 the leaderboard page for LVBench, published by zai-org. It is a Gradio app with its settings in constants.py, and it names the zai-org LVBench dataset. The README is only a configuration pointer, so it does not describe the benchmark itself.

Who it suits: Researchers and teams that evaluate models and want to see how they rank on LVBench.

Industry | Who uses it | How they use it | Example
AI research | Model researchers | Check how a model ranks on LVBench | Open the Space and read the board
Engineering | ML engineers | Compare candidate models before choosing one | Look up two models on the board
Education | Students | Read a benchmark's results in one place | Open the Space and scan the ranking

People who want the benchmark explained or documented can skip it, because the README gives no description.

Where to use it:

• A browser: the Space runs on Hugging Face with nothing to install
• Windows, macOS or Linux: run a copy of the Space with Python

Use case | Who | What they get back
View the board | Researchers | The LVBench leaderboard page
Read the code | Developers | A short Gradio app with its settings in constants.py

How to set it up:

• Python with pip on Windows, macOS or Linux
• The Python packages listed in requirements.txt
• Nothing at all if you only use the Space in a browser

1. Install the Hugging Face hub package.
2. Download the Space's files into a folder.
3. Move into that folder.
4. Install Gradio 5.46.1 and the packages from requirements.txt.
5. Start the app.

pip install -U huggingface_hub
hf download zai-org/LVBench --repo-type space --local-dir LVBench
cd LVBench
pip install gradio==5.46.1
pip install -r requirements.txt
python app.py

How to use it: Open the Space page in a browser, or start your own copy with the command below. The Gradio page that comes up is the leaderboard.

python app.py

Example: You open the Space to see where a model sits on the board. The page lists the results, and you read the ranking from there.

For newcomers and experts: If you are new, open the Space in a browser and read the board. Nothing needs installing, and the README has no further notes.

For experts, the repository is four files, app.py, constants.py, requirements.txt and the README, and the app runs on Gradio 5.46.1. The Space names the zai-org/LVBench dataset.

You open the Space
Gradio runs app.py
The page shows the leaderboard
You read the ranking

Good to know:

• License: mit
• Cost to run: none named
• Data it reaches: the zai-org/LVBench dataset it names
• Not for: none stated in the README

On Hugging Face, 13 November 2026

• Likes: 18
• Built with: gradio
• License: mit

Links

• Space: https://huggingface.co/spaces/zai-org/LVBench
• Files: https://huggingface.co/spaces/zai-org/LVBench/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.