Objective To explore the feasibility of using a large language model to generate perioperative health education materials for laparoscopic cholecystectomy patients, providing a new approach for clinical health education.Methods The research team established a list of perioperative nursing issues for laparoscopic cholecystectomy patients based on evidence.The DeepSeek-R1 model was used for simulated consultations, and through human-machine dialogue, perioperative health education materials were generated.These materials were evaluated using the Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P) by 30 healthcare professionals （the healthcare group）, as well as 30 patients and their families （patient group）, with results visualized through a tool.Results The health education materials received a score of (85.81±1.44) points, with a compliance rate of 88.33%.The understandability score from the patient group was significantly higher than that of the healthcare group (P＜0.05).Conclusion Large language models can serve as an auxiliary tool for health education, providing support for healthcare providers in developing educational plans and content, improving the understandability and compliance rate of health education materials.