GPT-4o and OpenAI o1 Performance on the 2024 Spanish Competitive Medical Specialty Access Examination: Cross-Sectional Quantitative Evaluation Study

These findings highlight the excellent performance of GPT-4o and OpenAI o1 on the MIR 2024 examination, demonstrating consistent accuracy across medical subjects and question types. The integration of LLMs into medical education presents promising opportunities and is likely to reshape how students prepare for licensing examinations and change our understanding of medical education. Further research should explore how the wording, language, prompting techniques, and image-based questions can influence LLMs' accuracy, as well as evaluate the performance of emerging artificial intelligence models in similar assessments.

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Publication Details

Journal
JMIR Medical Education
Published
2026-01-12
DOI
https://doi.org/10.2196/75452
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

GPT-4o and OpenAI o1 Performance on the 2024 Spanish Competitive Medical Specialty Access Examination: Cross-Sectional Quantitative Evaluation Study

Carlos Carazo-Casas, Pedro José Fernández Esparcia, Pablo Gutiérrez-Bedia, Manuel Carpio et al.
JMIR Medical Education
Artificial Intelligence in Healthcare and Education
article

GPT-4o and OpenAI o1 Performance on the 2024 Spanish Competitive Medical Specialty Access Examination: Cross-Sectional Quantitative Evaluation Study

Carlos Carazo-Casas, Pedro José Fernández Esparcia, Pablo Gutiérrez-Bedia, Manuel Carpio, Mikel Isla-Jover, Pau Benito, Pablo González-Castro, Maria J Lapastora, Beatriz Carratalá, Iván Blay-Simón
article en

Abstract

These findings highlight the excellent performance of GPT-4o and OpenAI o1 on the MIR 2024 examination, demonstrating consistent accuracy across medical subjects and question types. The integration of LLMs into medical education presents promising opportunities and is likely to reshape how students prepare for licensing examinations and change our understanding of medical education. Further research should explore how the wording, language, prompting techniques, and image-based questions can influence LLMs' accuracy, as well as evaluate the performance of emerging artificial intelligence models in similar assessments.

JMIR Medical EducationVol. 12
Hospital Clínico San Carlos (ES), Hospital Universitario 12 De Octubre (ES), Madrid Health Service (ES), Hospital Universitario Doctor Peset (ES), Hospital de Cruces (ES), Santa Lucía University General Hospital (ES), Barcelona Institute for Global Health (ES), Hospital Universitario Virgen del Rocío (ES), Hospital Universitario Ramón y Cajal (ES)
Quality Education
Openalex Percentile: Top 90%
Artificial Intelligence in Healthcare and Education
DOIOpen Access PDFOpenAlex
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GPT-4o and OpenAI o1 Performance on the 2024 Spanish Competitive Medical Specialty Access Examination: Cross-Sectional Quantitative Evaluation Study — Carlos Carazo-Casas, Pedro José Fernández Esparcia, et al. · JMIR Medical Education (2026) | TGRS Research Map | TGRS