# Gaia2 and ARE: Empowering the community to study agents

DevFeed: [Gaia2 and ARE: Empowering the community to study agents](<https://devfeed.tech/articles/gaia2-and-are-empowering-the-community-to-study-agents-7209.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/gaia2>)

Author: Clémentine Fourrier; Grégoire Mialon; Maxime Lecanu; Pierre Andrews; Adrien Carreira; frere thibaud; Avijit Ghosh; Romain Froger; Dheeraj Mekala; Caroline Pascal

Published: 2025-09-22T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [gaia](<https://devfeed.tech/topics/gaia.md>), [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [Framework](<https://devfeed.tech/topics/framework.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [debugging](<https://devfeed.tech/topics/debugging.md>)

Tags: [agents](<https://devfeed.tech/tags/agents.md>), [apis](<https://devfeed.tech/tags/apis.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [collaboration](<https://devfeed.tech/tags/collaboration.md>), [complexity](<https://devfeed.tech/tags/complexity.md>), [dataset](<https://devfeed.tech/tags/dataset.md>), [debug](<https://devfeed.tech/tags/debug.md>), [evaluation](<https://devfeed.tech/tags/evaluation.md>), [gaia](<https://devfeed.tech/tags/gaia.md>), [leaderboards](<https://devfeed.tech/tags/leaderboards.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [reasoning](<https://devfeed.tech/tags/reasoning.md>), [simulation](<https://devfeed.tech/tags/simulation.md>), [time](<https://devfeed.tech/tags/time.md>)

## AI overview

The article introduces Gaia2, a harder follow-up to the GAIA benchmark for evaluating interactive AI agents. Gaia2 expands evaluation from read-only information retrieval to read-and-write tasks involving tool use, web browsing, ambiguous and time-sensitive instructions, controlled failures, adaptability, and agent-to-agent collaboration. It is released with the open Meta Agents Research Environments (ARE) framework, which supports running, debugging, and evaluating agents in customizable simulated real-world conditions.

## Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.