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Model Evaluation & Threat Research (METR) is a nonprofit research institute headquartered in Berkeley, California, dedicated to scientifically measuring whether and when AI systems might threaten catastrophic harm to society. The organization develops evaluation methodologies, benchmarks, and open-source tools used by AI developers, governments, and other safety organizations worldwide.
METR originated as ARC Evals, a team incubated within Paul Christiano's Alignment Research Center in 2022 when Beth Barnes joined from OpenAI to lead exploratory work on independent evaluations of cutting-edge AI models. After conducting some of the first independent evaluations of frontier models including GPT-4 and Claude, the team grew to become a majority of ARC's headcount. ARC Evals spun out as an independent organization in September 2023 and was formally renamed METR in December 2023, becoming a standalone 501(c)(3) nonprofit. The name METR references metrology, the science of measurement and its application…
METR's theory of change is that independent, scientifically rigorous evaluation of frontier AI capabilities is essential for informed decision-making about AI development. By developing and deploying standardized methods to measure dangerous autonomous capabilities before AI systems are released, METR enables AI developers, governments, and policymakers to understand risks and implement appropriate safeguards. Their work creates an evidence base that informs responsible scaling policies, government regulation, and voluntary commitments by AI labs. By making evaluation tools open-source and partnering with safety institutes worldwide, METR aims to establish a global infrastructure for AI safety testing that scales with the pace of AI development, ensuring humanity is informed before transformative AI systems are deployed.
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View on grantmaking.aiCanary is a multi‑year collaboration between METR and RAND, selected as part of The Audacious Project’s 2024 cohort, that aims to create a “canary in the coal mine” for dangerous AI capabilities. The project funds METR and RAND to design, validate, and operationalize evaluations that can detect when frontier AI models acquire high‑risk capabilities, such as enabling cyber or biological misuse or supporting runaway autonomy, so that developers and governments can respond before deployment. Canary’s work includes building science‑based tools and benchmarks, running evaluations on cutting‑edge models, and helping integrate these assessments into safety policies and regulatory frameworks for frontier AI.