AI Agent Benchmarks Are Broken

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We find that many agentic benchmarks have issues with task setup or reward design, leading to under- or overestimation of agents’ performance by up to 100%.

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Results of applying ABC on ten widely used AI agent benchmarks.

To make agentic evaluation rigorous, we introduce the Agentic Benchmark Checklist (ABC), a set of guidelines that we synthesized from our benchmark-building experience, a survey of best practices, and previously reported issues.

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Operational and conceptual processes of AI agent evaluation. Task and outcome validity are essential to ensure that benchmark results truly reflect agents’ capabilities.
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