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Comparative Performance of State-of-the-Art LLMs on the KDLE: A 2025 Benchmark Study.

Taejun Kim¹, Bong Chul Kim¹

¹Department of Oral and Maxillofacial Surgery, Daejeon Dental Hospital, Wonkwang University College of Dentistry, Daejeon, Republic of Korea.

International Dental Journal

|February 28, 2026

Summary

Four advanced large language models (LLMs) demonstrated strong performance on the Korean Dental Licensing Examination (KDLE), with three nearing human competency. However, limitations in visual interpretation persist, suggesting LLMs should supplement, not replace, human expertise in dental education.

Keywords:

Artificial intelligence Dentistry Examination questions Large language models

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Area of Science:

Artificial Intelligence in Dentistry
Medical Education Technology
Dental Diagnostics

Background:

Large Language Models (LLMs) are rapidly evolving.
Assessing LLM capabilities in specialized professional examinations is crucial.
The Korean Dental Licensing Examination (KDLE) provides a standardized benchmark for dental knowledge and reasoning.

Purpose of the Study:

To evaluate the diagnostic and reasoning abilities of four leading LLMs on the KDLE.
To determine the potential of these LLMs as supplementary educational tools in dentistry.
To compare the performance of different LLMs on a high-stakes dental examination.

Main Methods:

Four LLMs (ChatGPT-4o, Claude-4 Opus, Gemini 2.5 Pro, DeepSeek-V3) were tested on 642 official KDLE questions from 2024-2025.
Performance was assessed by overall accuracy, modality (text vs. image), and subject-specific analyses.
Statistical tests including Cochran's Q and McNemar's tests were employed for rigorous comparison.

Main Results:

All evaluated LLMs surpassed the KDLE passing threshold.
ChatGPT-4o, Claude-4 Opus, and Gemini 2.5 Pro achieved scores comparable to or exceeding human examinees.
LLMs performed better on text-based questions than image-based ones and showed variability across dental subjects.

Conclusions:

Contemporary LLMs exhibit significant diagnostic and reasoning competence on dental licensing exams.
Three of the four LLMs demonstrated near-human performance levels.
Limitations in visual interpretation and clinical reasoning necessitate continued human oversight, positioning LLMs as supplementary educational aids.