[Purpose/Significance] The development and application of AI models are subject to specific regulatory requirements covering tiered risk regulation and dynamic full-lifecycle governance, resulting in archiving characteristics distinct from those of conventional information management systems or platforms. Research on the archiving of AI models can keep pace with the evolving landscape of artificial intelligence and enrich both the theory and practice of archival management. [Method/Process] This paper took the General-Purpose AI Code of Practice as the research object. It applied the BERTopic model for topic identification to outline the requirements and major risks concerning the development and application of AI models in the Code of Practice, and employed the DeepSeek V4 model for content extraction to summarize the documents and materials formed for risk governance. Based on this, the paper systematically analyzed and interpreted the Code of Practice from three dimensions: emphasizing tiered risk regulation for AI models, implementing dynamic full-lifecycle governance, and discussed how archival institutions, as back-end management subjects, should actively respond to the above requirements and risks. [Result/Conclusion] Based on the above analysis, this paper proposes that archival institutions can advance the archiving of AI models from three dimensions: implementing tiered archiving matching risk governance, clarifying full-lifecycle archiving specifications, and optimizing the scope of records collection oriented toward risk management, to provide references for the domestic practice of AI models archiving in China.