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    <title>Inference on Hullabalooing</title>
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    <lastBuildDate>Wed, 21 Jan 2026 00:00:00 -0700</lastBuildDate>
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      <title>vLLM Inference on MI60</title>
      <link>https://cruver.ai/gpu-ai/posts/vllm-inference-mi60/</link>
      <pubDate>Wed, 21 Jan 2026 00:00:00 -0700</pubDate>
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      <description>&lt;p&gt;Production inference using vLLM with tensor parallelism across dual MI60 GPUs.&lt;/p&gt;&#xA;&lt;h2 id=&#34;why-vllm&#34;&gt;Why vLLM?&lt;a class=&#34;anchor&#34; href=&#34;#why-vllm&#34;&gt;#&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;p&gt;After evaluating Ollama, llama.cpp, and vLLM for MI60 inference, &lt;strong&gt;vLLM&lt;/strong&gt; emerged as the best choice:&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tensor Parallelism&lt;/strong&gt;: Native support for splitting large models across multiple GPUs. With dual MI60s (64GB total), I can run 70B parameter models that wouldn&amp;rsquo;t fit on a single GPU.&lt;/p&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;&#xA;&lt;p&gt;&lt;strong&gt;PagedAttention&lt;/strong&gt;: More efficient memory management, allowing higher GPU utilization (90%) without OOM errors.&lt;/p&gt;</description>
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