Economic Evaluations of Language Models
Language models perform economically valuable work, yet they are not currently assessed for how well they perform every economically valuable task. We introduce EconEvals as an open-source evaluation suite to measure capabilities relevant to tasks, work activities, and occupations in the US labor economy. We ground the evaluation suite in real user queries to language models where possible, and supplement these with synthetic data. Our evaluations improve coverage over OpenAI's GDPval benchmark, which is the existing state-of-the-art that covers 5% of US occupations, at 500x lower cost. Alongside benchmarks, we also introduce a simulation-based exposure measure to estimate how much time c...
| Authors | Alexander Wan, Stephane Hatgis-Kessell, Tomás Aguirre et al. |
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| Primary category | cs.CY |
| Published | 26 June 2026 |
| Last updated at source | 26 June 2026 |
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