An updated analysis of large language model performance on ophthalmology speciality examinations
Abstract
Large language models (LLMs) have evolved rapidly since their public release in November 2022, with recent iterations integrating multi-modal and advanced reasoning capabilities. As their deployment within healthcare expands, rigorous benchmarking is essential. In 2023, Raimondi et al. evaluated LLM performance on the Fellowship of Royal College of Ophthalmologists (FRCOphth) exams [ 1 ], the standard for independent practice in the United Kingdom. This study reports an updated benchmark of current-generation models, supplemented by a qualitative error analysis to examine cases of model failure.
Fields of Study & Subjects
Ophthalmology and Visual Health Research
Artificial Intelligence in Healthcare and Education
Retinal Imaging and Analysis
Publication details
- Journal / source
- Eye
- Publisher
- Springer Science and Business Media LLC
- Volume
- 40
- Issue
- 5
- Pages
- 572–574
- Publication date
- 30 January 2026
- Language
- EN