<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Ollama on Nalar</title>
    <link>https://nalar.dev/tags/ollama/</link>
    <description>Recent content in Ollama on Nalar</description>
    <generator>Hugo</generator>
    <language>en-us</language>
    <lastBuildDate>Sat, 19 Sep 2026 00:00:00 +0000</lastBuildDate>
    <atom:link href="https://nalar.dev/tags/ollama/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>Ollama Gemma 3 270M Memory Is More Than the Model File</title>
      <link>https://nalar.dev/ollama-gemma-3-270m-memory-beyond-model-file-size/</link>
      <pubDate>Sat, 19 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://nalar.dev/ollama-gemma-3-270m-memory-beyond-model-file-size/</guid>
      <description>&lt;p&gt;Ollama lists &lt;code&gt;gemma3:270m&lt;/code&gt; at about 292 MB. That number is useful for storage planning, but it is not a RAM requirement. It describes the packaged model data for the default Ollama variant, which uses Q8_0 quantization. Once inference starts, the runtime also needs memory for model metadata, execution buffers, token state, and the key-value cache used by attention.&lt;/p&gt;&#xA;&lt;p&gt;That distinction matters on small machines. A device with 512 MB of RAM may appear large enough when compared only with a 292 MB model file, yet the remaining memory must also accommodate Ollama and the operating system. The context configuration can move the total substantially.&lt;/p&gt;</description>
    </item>
  </channel>
</rss>
