[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"tag-長上下文":3},{"tag":4,"articles":10,"peer_article_count":11},{"id":5,"name":6,"slug":6,"article_count":7,"description_zh":8,"description_en":9},"87866137-c0da-4bc0-a289-aca4b3445de2","長上下文",7,"長上下文指模型能在同一次推理中保留更多文件、程式碼、對話與工具輸出，從 128K、256K 到百萬級 token 都是重點。它影響長文件分析、跨檔案編輯、代理式工作流與記憶壓縮策略，也直接牽動成本、延遲與幻覺風險。","Long context refers to models that can keep far more text in a single run, from 128K and 256K windows to million-token APIs. It matters for codebases, long documents, agent workflows, memory compression, and the tradeoffs between cost, latency, and reliability.",[],19]