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    <title>Memory on Experiment, Fail, Learn, Repeat</title>
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      <title>Fitting a 12B Model into Two Small CPU Nodes: Gemma 4 on Graviton with vLLM</title>
      <link>https://www.hairizuan.com/fitting-a-12b-model-into-two-small-cpu-nodes-gemma-4-on-graviton-with-vllm/</link>
      <pubDate>Mon, 02 Nov 2026 00:00:00 +0000</pubDate>
      
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      <description>&lt;p&gt;In the &lt;a href=&#34;https://www.hairizuan.com/dont-split-a-model-that-fits-one-pod-vs-two-for-gemma-on-cpu/&#34; &gt;last post&lt;/a&gt; I argued that you should not split a model that fits on one machine: the 1B model I benchmarked was faster, steadier and cheaper in a single pod. The flip side of that argument is the case where splitting is not a choice. When the weights do not fit, pipeline parallelism is how you run the model at all.&lt;/p&gt;</description>
      
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