AUTHOR=Zhu Zhenxing , Xie Jun , Zhou Longxin , Yang Chaoran , Li Feng 

TITLE=Evaluation of the accuracy and repeatability of Deepseek V3, Doubao, and Kimi1.5 in answering knowledge-related queries about chronic non-bacterial osteitis

JOURNAL=Frontiers in Artificial Intelligence

VOLUME=Volume 8 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1629149

DOI=10.3389/frai.2025.1629149

ISSN=2624-8212

ABSTRACT=BackgroundThere are significant differences in the diagnosis and treatment of chronic non-bacterial osteitis (CNO), and there is an urgent need for health education efforts to enhance awareness of this condition. Deepseek V3, Doubao, and Kimi1.5 are highly popular language models in China that can provide knowledge related to diseases. This article aims to investigate the accuracy and reproducibility of the responses provided by these three artificial intelligence (AI) language models in answering questions about CNO.MethodsAccording to the latest expert consensus, 16 questions related to CNO were collected. The three AI language models were separately asked these questions at three different times. The answers were independently evaluated by two orthopedic experts.ResultsAmong the responses of the three AI models to 16 CNO-related questions across three rounds of testing, only Doubao received “Completely incorrect” ratings (accounting for 6.25%) in the third round of scoring by Reviewer 2. During the answering process, Doubao had the shortest response time and provided the most words in its answers. In the first and third rounds of scoring by the first expert, Kimi scored the highest (3.938 ± 0.342, 3.875 ± 0.873), while in the second round, Doubao scored the highest (3.875 ± 0.5). In the second round of scoring by the second expert, Doubao received the highest score (3.812 ± 0.403). In the first and third rounds, Kimi1.5 received the highest score (3.812 ± 0.602, 3.812 ± 0.704).ConclusionDeepseek V3, Doubao, and Kimi1.5 are capable of answering most questions related to CNO with good accuracy and reproducibility, showing no significant differences.