Artificial Intelligence in Gastroenterology Education: DeepSeek Passes the Gastroenterology Board Examination and Outperforms Legacy ChatGPT Models

INTRODUCTION: DeepSeek was evaluated in gastroenterology board examination performance against legacy ChatGPT offline models, which previously showed failing performance. METHODS: The performances of the DeepSeek base R1 model and search-augmented R1 model were assessed using American College of Gastroenterology self-assessments (455 questions). RESULTS: DeepSeek exceeded passing threshold. Search-augmented DeepSeek scored 81.5% across all questions, and the R1 base model scored 77.1%. Both search-augmented and offline DeepSeek models surpassed offline ChatGPT-3 (65.1%) and ChatGPT-4 (62.4%) (p < 0.001). DISCUSSION: DeepSeek exhibited passing performance on the gastroenterology board examination, but gaps in niche topics and image exclusion limit utility. It may supplement education if validated by specialists.