Artificial intelligence (AI) technology is deeply revolutionizing the medical education model. The DeepSeek-R1 large language model, with its open-source nature, hybrid expert architecture and complex reasoning ability, provides a new path to break through the traditional bottleneck for case-based learning (CBL) in nephrology education. Traditional CBL faces challenges such as scarce case resources, insufficient personalized guidance and low teaching efficiency during nephrology internships. DeepSeek can empower CBL through dynamic case generation, intelligent interactive question and answer, and precise scoring and evaluation. It not only significantly improves teachers′ teaching efficiency, but also effectively exercises students' clinical decision-making ability. However, key challenges such as AI reliance, data privacy, and the training of teachers and students should be dealt with caution. In the future, virtual reality multimodal technology can be further integrated, and a cross-school case sharing system can be constructed. This AI-integrated CBL model is expected to become one of the core teaching tools for cultivating high-quality clinical nephrology specialists.