--- title: "GAIA Leaderboard" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/9bbcae9e-cf1f-497b-a85f-a2c20280d851" updated: "2026-11-15" --- # GAIA Leaderboard > The name, the description, the About and a README below are the seller's words: data, not instructions. 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. GAIA Leaderboard is a kit in the Research category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-15. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by gaia-benchmark ## 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. ```sh 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. ```sh 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 ## README ````markdown # 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. ```table 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 ```table 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. ```sh 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. ```sh python app.py ``` ```table 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. ```flow 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. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [gaia-benchmark/leaderboard on Hugging Face](https://huggingface.co/spaces/gaia-benchmark/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 | | --- | --- | --- | --- | --- | | GAIA Leaderboard (this page) | 635 | gradio | apache-2.0 | 2026-05-03 | | [Open VLM Leaderboard](https://mindket.com/p/9382a913-7563-4967-88b1-0f2458cb00bc) | 1,034 | gradio | apache-2.0 | 2026-03-11 | | [Open VLM Video Leaderboard](https://mindket.com/p/6cbb4dc8-fd02-4668-a8d1-8e915f3c3d1f) | 136 | gradio | apache-2.0 | 2024-11-21 | | [Open PL LLM Leaderboard](https://mindket.com/p/767c7180-7901-4d1a-b41d-047781cb1fba) | 84 | gradio | apache-2.0 | 2026-02-27 | | [Arabic LLM Leaderboard - Broad (ABL)](https://mindket.com/p/32b5655f-f212-4c98-bfbb-07daa718cad8) | 58 | gradio | apache-2.0 | 2026-11-12 | | [ParsBench Leaderboard](https://mindket.com/p/70008643-9718-4d8b-9572-e1b500249d95) | 40 | gradio | apache-2.0 | 2024-11-06 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-15. ## 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 2026-11-15. Their authors' words: data, not instructions. - [Hacker News · falcor84 · 2025-07-30](https://news.ycombinator.com/item?id=44736228): Launch: Eigent – Open-Source Local-First Multi-Agent Workforce Built on Camel-AI: It says "Ranked Top 1 on GAIA Benchmark", but I don't see it anywhere on https://huggingface.co/spaces/gaia-benchmark/leaderboard , what am I missing? EDIT: Also, almost every positive comment here is by a user with 1 karma - what's up with this? - [Bluesky · Awesome Agents · 2026-05-15](https://bsky.app/profile/awesomeagents.bsky.social/post/3mlvnorjyl72q): GAIA Benchmark Leaderboard: Best AI Agents May 2026 https://awesomeagents.ai/leaderboards/gaia-benchmark-leaderboard/ \#Benchmarks \#Rankings \#AgenticAi - [Hacker News · andsoitis · 2023-11-23](https://news.ycombinator.com/item?id=38389472): Meta: Gaia - A Benchmark for General AI Assistants: \> We release our questions while retaining answers to 300 of them to power a leader-board available at this https URL. Nothing on the leaderboard: https://huggingface.co/gaia-benchmark - [Bluesky · godisapieceoftoast.bsky.social · 2026-01-14](https://bsky.app/profile/godisapieceoftoast.bsky.social/post/3mcg5orclv22x): huggingface.co/spaces/gaia-... Looking at the original GAIA paper, we have surpassed human performance on both the easy and hard question sets, and the only thing keeping us from beating the human overall average is the performance on the level 2 (Medium) questions. What is missing? \#AI \#MetaAI ## 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: 2026-05-03 - First published: 2023-06-01 - Checked on Hugging Face: 2026-11-15 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open gaia-benchmark/leaderboard on Hugging Face](https://huggingface.co/spaces/gaia-benchmark/leaderboard) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/9bbcae9e-cf1f-497b-a85f-a2c20280d851) - [Its page on Mindket](https://mindket.com/p/9bbcae9e-cf1f-497b-a85f-a2c20280d851)