[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-推論成本":3},{"tag":4,"articles":10,"peer_article_count":11},{"id":5,"name":6,"slug":6,"article_count":7,"description_zh":8,"description_en":9},"4f2b3013-a727-4196-b25f-a2f32866dfcd","推論成本",6,"推論成本指的是模型在實際服務時，每次生成、回應或代理執行所消耗的算力、記憶體、延遲與雲端費用。從 GPU\u002FCPU 架構、模型大小到批次與快取策略，這些取捨直接影響 AI 產品能否規模化。","Inference cost is the ongoing compute, memory, latency, and cloud spend required when a model serves real requests. It shapes choices around GPU and CPU architecture, model size, batching, and caching, and it often determines whether AI products can scale economically.",[],7]