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    <title>Scaling on Tyler Zhu</title>
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    <description>Recent content in Scaling on Tyler Zhu</description>
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      <title>Have we scaled vision like language yet?</title>
      <link>https://tylerzhu.com/blog/2026/02/have-we-scaled-vision-like-language-yet/</link>
      <pubDate>Sat, 14 Feb 2026 23:32:00 +0800</pubDate>
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      <description>&lt;p&gt;A few years ago at our &lt;a href=&#34;https://sites.google.com/view/t4v-cvpr23?pli=1&#34;&gt;CVPR 2023 Transformers for Vision workshop&lt;/a&gt;, Lucas Beyer said something that struck me by surprise. I&amp;rsquo;ve been trying to piece it together ever since.&lt;/p&gt;
&lt;p&gt;The interaction went something like this:&lt;/p&gt;
&lt;blockquote&gt;
&lt;p&gt;&lt;strong&gt;Audience:&lt;/strong&gt; &amp;ldquo;Why aren&amp;rsquo;t we scaling vision models as large as we do LLMs?&amp;rdquo;&lt;/p&gt;
&lt;/blockquote&gt;
&lt;blockquote&gt;
&lt;p&gt;&lt;strong&gt;Lucas:&lt;/strong&gt; &amp;ldquo;You know, actually, the largest vision models are on par with the largest language models if you look at [X].&amp;rdquo;&lt;/p&gt;
&lt;/blockquote&gt;
&lt;p&gt;I can never quite remember what X was — FLOPs, parameters, or token budget. Obviously now it&amp;rsquo;s not parameters. The largest recorded ViTs still tap out in the 22B regime, with the most consistent scaling amounts being 1B–7B as in DINOv3 &lt;a href=&#34;#ref-10&#34;&gt;[10]&lt;/a&gt;.&lt;/p&gt;</description>
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