<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>成本 on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/tags/%E6%88%90%E6%9C%AC/</link><description>Recent content in 成本 on 硅基 AGI · 智能体学习与测评</description><generator>Hugo</generator><language>zh-cn</language><copyright>本站内容采用 CC BY-NC-SA 4.0 国际许可协议授权</copyright><lastBuildDate>Thu, 02 Jul 2026 10:26:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/%E6%88%90%E6%9C%AC/index.xml" rel="self" type="application/rss+xml"/><item><title>2026年AI模型价格战：API降价90%</title><link>https://guijiagi.com/posts/ai-model-price-war-2026/</link><pubDate>Thu, 02 Jul 2026 10:26:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-model-price-war-2026/</guid><description>2026年AI模型API价格暴跌90%，推动AI应用普及</description></item><item><title>小模型vs大模型成本效益分析</title><link>https://guijiagi.com/posts/small-vs-large-model-cost/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/small-vs-large-model-cost/</guid><description>小模型vs大模型成本效益分析</description></item><item><title>LLM 成本优化实战：10 种降低 API 费用的方法</title><link>https://guijiagi.com/posts/llm-cost-optimization/</link><pubDate>Thu, 25 Jun 2026 12:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-cost-optimization/</guid><description>从模型选择、Prompt 精简、缓存策略到流量路由，系统介绍 10 种可落地的 LLM API 成本优化方法，附带代码示例与量化对比。</description></item><item><title>AI 成本优化策略：从 Token 到基础设施的全链路省钱</title><link>https://guijiagi.com/posts/ai-cost-optimization-strategy/</link><pubDate>Thu, 25 Jun 2026 10:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/ai-cost-optimization-strategy/</guid><description>系统性分析 LLM 应用的成本结构，涵盖 Token 优化、模型路由、缓存策略、Batch API 到基础设施层的全链路降本实践</description></item></channel></rss>