Abstract: With the deepening application of artificial intelligence (AI) technology in the field of medical devices, pre-trained models have increasingly become a crucial engine driving innovation in intelligent healthcare due to their efficiency, generalization capability, and transfer learning performance. However, potential risks associated with pre-trained models—such as issues related to source diversity and quality controllability —pose new challenges to the safety and effectiveness of AI-based medical devices. Against this background, the National Medical Products Administration (NMPA) released the sectoral standard YY/T 1833.5-2024 Artificial Intelligence Medical Devices—Quality Requirements and Evaluation-Part 5: Pre-trained Models in September 2024. This standard provides essential technical guidance and a regulatory framework for standardizing the application of pre-trained models in medical devices, marking a milestone in ensuring the safety and efficacy of AI-powered medical products. This article offers an in-depth interpretation and analysis of the standard's background, orientation, and key technical consideration. It elucidates specific requirements regarding documentation for pre-trained models, definitions of critical quality attributes, and conformity assessment pathways. Furthermore, the practical and far-reaching implications of the standard are discussed, including its role in enhancing quality assurance throughout the entire lifecycle of AI-based medical devices and guiding technological innovation and healthy development within the industry. Additionally, by dissecting the standard, this article aims to support the industry in conducting prudent evaluations during model selection phases, thereby reducing the application of low-quality and high-risk models.