Open Agent Leaderboard
What it is
A benchmarking framework and leaderboard for evaluating language agent performance across different datasets and LLMs. It utilizes a graph-based orchestration engine (AGORA) to provide a modular and scalable way to assess agent reasoning and action capabilities.
The problem it solves
Lack of fair and consistent evaluation methods for language agents across diverse datasets and models.
What you could use it for
- Benchmarking LLM performance on math tasks (GSM8K, AQuA, MATH-500)
- Comparing different reasoning algorithms like CoT, ReAct, and ToT
- Evaluating multiple LLMs (e.g., GPT-4o, Llama-3.3, Qwen) on a unified platform
Read the source ↗Back to the library →
Summary written by an AI model from the source; check the source before you rely on it.