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        <title>Jetson - Tag - David Vincze</title>
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    <title>Edge Inference Benchmark Lab — FP32 vs FP16 vs INT8 on Jetson Orin Nano: What Do You Actually Gain?</title>
    <link>https://davidvincze.com/posts/edge-inference-benchmark-lab/</link>
    <pubDate>Sun, 27 Sep 2026 09:00:00 &#43;0200</pubDate>
    <author>contact@davidvincze.com (David Vincze)</author>
    <guid>https://davidvincze.com/posts/edge-inference-benchmark-lab/</guid>
    <description><![CDATA[<h2 id="introduction">Introduction</h2>
<p>This article is adressed to fellow Edge AI enthusiasts, engineers and researchers.</p>
<p>This is the first part of my new Physical AI series focusing on efficient model deployment on edge devices. This will be a journey for me and hopefully for you, the reader, too. My goal through this series is to contribute with useful insights in an emergind domain and to give you some take away for your own projects, such as the approach, the hardware constraints, the architectural thinking, the data used, or the lessons learned along the way.</p>]]></description>
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