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    <title>NVIDIA on ZML - Model to Metal</title>
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      <title>ZML/LLMD alpha</title>
      <link>https://zml.ai/posts/llmd/</link>
      <pubDate>Wed, 08 Jul 2026 08:00:00 +0100</pubDate>
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      <description>&lt;p&gt;Today we&amp;rsquo;re releasing ZML/LLMD. It&amp;rsquo;s a self-contained inference server that runs LLaMa, Gemma, Qwen and Mistral LLMs&#xA;transparently on &lt;strong&gt;5 architectures&lt;/strong&gt;: &lt;strong&gt;NVIDIA CUDA&lt;/strong&gt;, &lt;strong&gt;AMD ROCm&lt;/strong&gt;, &lt;strong&gt;Google TPU&lt;/strong&gt;, &lt;strong&gt;Intel oneAPI&lt;/strong&gt; and &lt;strong&gt;Apple&#xA;Metal&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&#34;https://zml.ai/posts/llmd/llmd1.png&#34; alt=&#34;&#34;&gt;&#xA;&lt;/p&gt;&#xA;&lt;h2 id=&#34;modern-serving-features&#34;&gt;Modern serving features&lt;/h2&gt;&#xA;&lt;p&gt;ZML/LLMD supports modern serving features: &lt;strong&gt;continuous batching&lt;/strong&gt;, &lt;strong&gt;paged attention&lt;/strong&gt;, &lt;strong&gt;tensor parallel sharding&lt;/strong&gt;,&#xA;&lt;strong&gt;prefix caching&lt;/strong&gt;, &lt;strong&gt;tool calling&lt;/strong&gt; and does so on &lt;strong&gt;all platforms&lt;/strong&gt;.&lt;/p&gt;&#xA;&lt;p&gt;Metrics are also exposed in the Prometheus format via the &lt;code&gt;/metrics&lt;/code&gt; endpoint.&lt;/p&gt;</description>
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