GAIA Leaderboard

GAIA Leaderboard

Shows a leaderboard built around the GAIA dataset, so people can compare AI systems on one shared benchmark. It is a Gradio app from the gaia-benchmark group.

Made by gaia-benchmark 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: GAIA Leaderboard is a Gradio app from the gaia-benchmark group. It presents a leaderboard tied to the GAIA dataset, which the Space names on Hugging Face. The repository holds app.py along with content.py and scorer.py, and it runs on the cpu-upgrade hardware setting.

Who it suits: People who follow or take part in AI benchmarks and want one page where results on the GAIA dataset are gathered.

Industry | Who uses it | How they use it | Example
Research | AI researchers | Check where systems stand on a shared benchmark | Look through the entries on the leaderboard
Software | Teams building AI assistants | Compare their results with others | Read the ranking before a release
Education | Students of machine learning | Learn how a leaderboard is put together | Read app.py and scorer.py

People who need a tool for building or running an AI assistant can skip it, since this page ranks results.

Where to use it:

• A browser, by visiting the Space on Hugging Face
• Windows, macOS or Linux with Python, for a copy on your own computer
• A local Gradio page, once app.py is running

Use case | Who | What they get back
View the leaderboard | Researchers | A ranked page of results on the GAIA dataset
Study the code | Developers | A small Gradio project with a scoring file

How to set it up:

• Python and pip on Windows, macOS or Linux
• The Python packages in requirements.txt
• Gradio 5.49.1, the version the Space uses

1. Install the Hugging Face hub package.
2. Download the Space with the hf command.
3. Move into the new folder.
4. Install gradio at the version the Space uses, then the listed packages.
5. Start the app with Python.

pip install -U huggingface_hub
hf download gaia-benchmark/leaderboard --repo-type space --local-dir leaderboard
cd leaderboard
pip install gradio==5.49.1
pip install -r requirements.txt
python app.py

How to use it: Online, visit the Space on Hugging Face and read the leaderboard that loads. On your own computer, run the start command and open the local page Gradio serves.

python app.py

Tool | What it does
app.py | Starts the Gradio interface
scorer.py | A scoring file kept beside the app
content.py | A support file kept beside the app
requirements.txt | Lists the Python packages to install

Example: You visit the Space, open the leaderboard, and look at how the listed entries rank against each other on the GAIA dataset.

For newcomers and experts: If you are new, visit the Space and read the table. A leaderboard is a ranked list that lets you see at a glance how different systems did on the same set of questions.

If you know the field, the repository is only a handful of files, with the page logic in app.py and a separate scorer.py. The Space names the gaia-benchmark/GAIA dataset and runs on the cpu-upgrade hardware setting, so no GPU is involved. The trade-off is that the source gives few details of how scoring works.

You visit the Gradio page
app.py builds the leaderboard
The GAIA dataset is named as its data
You read and compare the entries

Good to know:

• Hardware: the Space is set to cpu-upgrade, so no GPU is named
• Detail: the source says little about how entries are submitted or scored
• License: apache-2
• Cost to run: none named
• Data it reaches: the gaia-benchmark/GAIA dataset on Hugging Face

On Hugging Face, 15 November 2026

• Likes: 635
• Built with: gradio
• License: apache-2.0

Links

• Space: https://huggingface.co/spaces/gaia-benchmark/leaderboard
• Files: https://huggingface.co/spaces/gaia-benchmark/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.