ArticleJMIR medical education2025
Evaluating the Performance of DeepSeek-R1 and DeepSeek-V3 Versus OpenAI Models in the Chinese National Medical Licensing Examination: Cross-Sectional Comparative Study.
Article in JMIR medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
- Large Language Model Performance on Multistep Clinical Cases: Comparative Study Across Question and Case Levels.JMIR medical education · 2026Article
- Mapping the Reliability-Readability Gap in the Education of Patients With Age-Related Macular Degeneration Across 6 Large Language Models: Comparative Evaluation Study.JMIR medical informatics · 2026Article
- The Performance of ChatGPT-4o and DeepSeek-R1 in Interpreting Thyroid Nodule Ultrasound Text Reports: Multicenter Study.Journal of medical Internet research · 2026Article
- A comparative study of the performance of different large language models in the Chinese National Pharmacist Licensing Examination.Frontiers in medicine · 2026Article
- Evaluating the performance of DeepSeek-V3, Doubao, ERNIE 4.5 Turbo and iFLYTEK Spark in the Chinese national nursing licensing examination: a cross-sectional comparative study.Frontiers in artificial intelligence · 2026Article
- Comprehensive Evaluation of Large Language Models on Four Core Medical School Courses: A Cross-Sectional Comparative Study.Advances in medical education and practice · 2026Article
- Performance of deepseek-R1 and ChatGPT-5.4 thinking in the medical laboratory professional title examination: accuracy, stability, and comparison with interns.Frontiers in digital health · 2026Article
- Performance stability despite iteration: evaluating DeepSeek and ChatGPT on Chinese medical licensing examinations.Frontiers in medicine · 2026Article
- Large language models for breast cancer treatment planning: a blinded real-world evaluation of DeepSeek, ChatGPT, and oncologist recommendations.Frontiers in digital health · 2026Article
- Benchmarking large language models on a Chinese radiation oncology technology examination-preparation question set: accuracy, consensus, and efficiency for AI assisted education.Frontiers in oncology · 2026Article
- Evaluation of Few-Shot AI-Generated Feedback on Case Reports in Physical Therapy Education: Mixed Methods Study.JMIR medical education · 2025Article
- Comparative performance of ChatGPT and DeepSeek in interpreting the 2025 ESICM guidelines on sepsis fluid therapy.Digital healthArticle
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Abstract
backgroundDeepseek-R1, an open-source large language model (LLM), has generated significant global interest in the past months.
objectiveThis study aimed to compare the performance of DeepSeek and OpenAI LLMs on the Chinese National Medical Licensing Examination (NMLE) and evaluate their potential in medical education.
methodsThis cross-sectional study assessed 2 DeepSeek models (DeepSeek-R1 and DeepSeek-V3), 3 OpenAI models (ChatGPT-o1 pro, ChatGPT-o3 mini, and GPT-4o), and 2 additional Chinese LLMs (ERNIE 4.5 Turbo and Qwen 3) using the 2021 NMLE. Model performance was evaluated based on overall accuracy, accuracy across question types (A1, A2, A3 and A4, and B1), case analysis and non-case analysis questions, medical specialties, and accuracy consensus between different model combinations.
resultsAll LLMs successfully passed the NMLE. DeepSeek-R1 achieved the highest accuracy (573/597, 96%), followed by DeepSeek-V3 (558/600, 93%), both of which significantly outperformed ChatGPT-o1 pro (450/600, 75%), ChatGPT-o3 mini (455/600, 75.8%), and GPT-4o (452/600, 75.3%; P<.001 for all comparisons). Performance disparities were consistent across various question types (A1, A2, A3 and A4, and B1), case analysis and non-case analysis questions, different types of case analyses, and medical specialties. The accuracy consensus between DeepSeek-R1 and DeepSeek-V3 reached 97.7% (544/557), significantly outperforming DeepSeek-R1 alone (P=.04). Two additional Chinese LLMs, ERNIE 4.5 Turbo (572/600, 95.3%) and Qwen 3 (555/600, 92.5%), also exhibited significantly better performance compared to the 3 OpenAI models (all P<.001).
conclusionsThis study demonstrates that DeepSeek-R1 and DeepSeek-V3 significantly outperform OpenAI models on the NMLE. DeepSeek models show promise as tools for medical education and exam preparation in the Chinese language.
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