<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Local-Models on Engineering Notes</title><link>https://notes.muthu.co/tags/local-models/</link><description>Recent content in Local-Models on Engineering Notes</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Wed, 01 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://notes.muthu.co/tags/local-models/index.xml" rel="self" type="application/rss+xml"/><item><title>Local-First LLM Routing - Use Small Models for Easy Questions and Cloud Models for Hard Ones</title><link>https://notes.muthu.co/2026/07/local-first-llm-routing-use-small-models-for-easy-questions-and-cloud-models-for-hard-ones/</link><pubDate>Wed, 01 Jul 2026 00:00:00 +0000</pubDate><guid>https://notes.muthu.co/2026/07/local-first-llm-routing-use-small-models-for-easy-questions-and-cloud-models-for-hard-ones/</guid><description>&lt;p>Every LLM call costs something.&lt;/p>
&lt;p>Sometimes the cost is money. Sometimes it is latency. Sometimes it is privacy.&lt;/p>
&lt;p>If you send every request to a frontier model, you burn budget on tasks a small local model could have handled. If you run everything locally, the easy cases feel great until a harder reasoning task shows up and the answer falls apart.&lt;/p>
&lt;p>The better pattern is a &lt;strong>local-first routing gateway&lt;/strong>.&lt;/p>
&lt;p>Put a thin layer between your chat UI and your models. The gateway looks at each request, sends simple work to a local model, and escalates harder work to a remote model. The user still sees one assistant. The system decides which model should answer.&lt;/p></description></item></channel></rss>