Today we're launching the Open Agent Leaderboard, an open benchmark for comparing full agent systems, not just the models inside them. It reports both quality and cost, so you can see not just what works, but what's worth deploying.

The leaderboard is paired with the Exgentic framework for running and reproducing evaluations, and a paper describing the full methodology and results. Everything is open from day one.

AI agents are getting really useful when carefully tailored to a specific job, like coding in a familiar repository or handling customer service with a known set of tools. But the harder question is whether the same agent can handle many different jobs, each with its own tools, rules, and constraints, without being manually customized for each one.

A more general agent is one you can drop into a new setting and have it just work.