<?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>报价模型 on AI 实战派 · 从技术到赚钱</title><link>https://guijiagi.com/tags/%E6%8A%A5%E4%BB%B7%E6%A8%A1%E5%9E%8B/</link><description>Recent content in 报价模型 on AI 实战派 · 从技术到赚钱</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, 08 Oct 2026 14:42:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/%E6%8A%A5%E4%BB%B7%E6%A8%A1%E5%9E%8B/index.xml" rel="self" type="application/rss+xml"/><item><title>长任务 Agent 怎么收费：按任务报价的实操公式</title><link>https://guijiagi.com/posts/2026-10-08-per-task-agent-pricing/</link><pubDate>Thu, 08 Oct 2026 14:42:00 +0800</pubDate><guid>https://guijiagi.com/posts/2026-10-08-per-task-agent-pricing/</guid><description>Manus 式长任务智能体正在替代按 token 计费。本文给出一套可复制的按任务定价公式，把模型成本、重试损耗和利润一次算清。</description></item></channel></rss>