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    <title>The Minutes of Dylan Patel on deepseek</title>
    <link>https://minutesof.com/dylan-patel/on/deepseek/</link>
    <description>Everything Dylan Patel has said on deepseek: 9 verbatim quotes between February 2025 and August 2026, each with a timestamp and a link to the recording it…</description>
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      <title>Patel claims hardware improved 30x from Hopper to Blackwell for DeepSeek on optimized deployments.</title>
      <link>https://minutesof.com/q/1aeaaf0c-1080-4d21-a79c-2bc3d127baf5/</link>
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      <description>“from Hopper to Blackwell, which is all we&#x27;ve had over the last three years, roughly 30x improvement on DeepSeek, on the most optimized deployment, which you can see on InferenceX there&#x27;s about a 30x improvement.” — Sequoia Capital</description>
      <pubDate>Tue, 30 Jun 2026 12:00:25 +0000</pubDate>
      <category>deepseek</category>
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      <title>Patel cites DeepSeek&#x27;s open-sourced inference system requiring 140 GPUs communicating over RDMA networks for s</title>
      <link>https://minutesof.com/q/b5b15eca-a046-4a24-8309-0cfa9d92ceec/</link>
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      <description>“One example is one that DeepSeek open sourced over December of last yearJanuary, February of this year, where a single replica of inference for a single model is going to be like 140 GPUs.” — Clockwork</description>
      <pubDate>Fri, 21 Nov 2025 17:18:51 +0000</pubDate>
      <category>deepseek</category>
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      <title>Patel reveals DeepSeek inference implementation requires 160 GPUs worth over $10 million of hardware per repli</title>
      <link>https://minutesof.com/q/13cb1933-7756-463f-ac46-7f8cd066bee0/</link>
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      <description>“That&#x27;s over $10,000,000 of hardware, and then that&#x27;s just one replica, then you&#x27;ll have a lot of replicas and you share the caching servers between them.” — No Priors: AI, Machine Learning, Tech, &amp; Startups</description>
      <pubDate>Thu, 14 Aug 2025 10:01:35 +0000</pubDate>
      <category>deepseek</category>
    </item>
    <item>
      <title>Patel reports GPT-3 to Llama 3.2 costs fell 1,200x while GPT-4 to DeepSeek v3 costs fell 600x.</title>
      <link>https://minutesof.com/q/c28a19fc-d8f5-4e4a-bc59-e7dabb126c8c/</link>
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      <description>“when we looked at g p d three, the cost fell 1,200 x from g p d three&#x27;s initial cost to what you can get Lama 3.23 b today.” — Alex Kantrowitz</description>
      <pubDate>Wed, 23 Apr 2025 16:30:06 +0000</pubDate>
      <category>deepseek</category>
    </item>
    <item>
      <title>Patel says DeepSeek&#x27;s cost efficiency follows the expected trend line, just from an unexpected source.</title>
      <link>https://minutesof.com/q/42277ecd-5d1b-4270-a90f-11eb7f3a67b8/</link>
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      <description>“It&#x27;s not unexpected. Right? Like, this is actually within the trend line of what happened with GPT three is happening to GPT four level quality with DeepSeq.” — Alex Kantrowitz</description>
      <pubDate>Wed, 23 Apr 2025 16:30:06 +0000</pubDate>
      <category>deepseek</category>
    </item>
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      <title>Patel challenges DeepSeek&#x27;s GPU count claims, citing job ads promising tens of thousands of GPUs.</title>
      <link>https://minutesof.com/q/c235c852-3da5-495d-8118-6bceb59270eb/</link>
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      <description>“The estimates that we have is, so first of all, ads in China, they say they have tens of thousands of GPUs for researchers, right?” — Special Competitive Studies Project</description>
      <pubDate>Thu, 13 Mar 2025 16:42:15 +0000</pubDate>
      <category>deepseek</category>
    </item>
    <item>
      <title>Patel explains DeepSeek v3 base is trained once, then post-trained differently to create chat versus reasoning</title>
      <link>https://minutesof.com/q/02fd4a40-e301-43f7-be83-33801b8010a9/</link>
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      <description>“This reasoning model has a lot of overlapping training steps to DeepSeek v three, and it&#x27;s confusing that you have a base model called v three that you do something to to get a chat model, and then you do some different things to get a reasoning model.” — Lex Fridman</description>
      <pubDate>Mon, 03 Feb 2025 00:12:13 +0000</pubDate>
      <category>deepseek</category>
    </item>
    <item>
      <title>Patel says DeepSeek modifies code at or below NVIDIA&#x27;s CUDA layer, a rare technical capability.</title>
      <link>https://minutesof.com/q/99d651cc-75d0-4621-9e78-21bd90eeb8aa/</link>
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      <description>“For example, on their to get highly efficient training, they&#x27;re making modifications at or below the CUDA layer for NVIDIA chips.” — Lex Fridman</description>
      <pubDate>Mon, 03 Feb 2025 00:12:13 +0000</pubDate>
      <category>deepseek</category>
    </item>
    <item>
      <title>Patel notes DeepSeek&#x27;s routing innovation removing auxiliary loss represents compounding small improvements ov</title>
      <link>https://minutesof.com/q/fab5c10d-e2cd-4e52-b056-9586751d1efb/</link>
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      <description>“this type of change can be big, it can be small, but they add up over time.” — Lex Fridman</description>
      <pubDate>Mon, 03 Feb 2025 00:12:13 +0000</pubDate>
      <category>deepseek</category>
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