Performance of Open-Source LLMs in Challenging Radiological Cases – A Benchmark Study on 4,049 Eurorad Case Reports

Abstract

Background Recent advancements in large language models (LLMs) have created new ways to support radiological diagnostics. While both open-source and proprietary LLMs can address privacy concerns through local or cloud deployment, open-source models provide advantages in continuity of access, independence from commercial update cycles, and potentially lower costs.