<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Model Selection on Mohammad Movahedi</title><link>https://m-movahedi.com/tags/model-selection/</link><description>Recent content in Model Selection on Mohammad Movahedi</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Sat, 30 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://m-movahedi.com/tags/model-selection/index.xml" rel="self" type="application/rss+xml"/><item><title>Local LLMs 203: Choosing a Model Without Guessing</title><link>https://m-movahedi.com/scratchpad/local-llms/local-llms-203-choosing-a-local-llm-without-guessing/</link><pubDate>Sat, 30 May 2026 00:00:00 +0000</pubDate><guid>https://m-movahedi.com/scratchpad/local-llms/local-llms-203-choosing-a-local-llm-without-guessing/</guid><description>&lt;p&gt;Local model choice can turn into name collecting very quickly. Llama, Qwen, Gemma, Mistral, DeepSeek, Phi, gpt-oss, coder models, reasoning models, small models, giant models, quantized models, preview models: it is a lot.&lt;/p&gt;
&lt;p&gt;The goal is not to memorize every release. The goal is to choose a model with a reason.&lt;/p&gt;
&lt;h2 id="mental-model-model-choice-is-task-fit-plus-hardware-fit"&gt;Mental model: model choice is task fit plus hardware fit&lt;/h2&gt;
&lt;p&gt;A useful model is the intersection of three things:&lt;/p&gt;</description></item></channel></rss>