Researchers are benchmarking large language models on medical licensing examinations to evaluate their clinical reasoning and decision-making abilities. The models are being compared to human teams and specialized clinical AI tools, with some studies suggesting they can match or outperform them in certain tasks. The benchmarks are being developed and tested by various institutions, including Stanford, to assess the models' capabilities in areas such as data analysis and personalized health intervention recommendations.