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        <title>Clint Johnson — LLM architecture</title>
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        <description>Articles tagged LLM architecture by Clint Johnson.</description>
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            <title><![CDATA[The Open-Weight LLM Landscape in 2026: What Engineers Actually Need to Know]]></title>
            <link>https://www.clint-johnson.com/articles/open-weight-llm-trends</link>
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            <pubDate>Sun, 15 Feb 2026 00:00:00 GMT</pubDate>
            <description><![CDATA[The open-weight ecosystem has matured faster than most engineers realize. MoE proliferation, hybrid attention, and extended context windows are changing what's deployable on-premise. That matters more than ever for healthcare AI.]]></description>
            <content:encoded><![CDATA[The open-weight ecosystem has matured faster than most engineers realize. MoE proliferation, hybrid attention, and extended context windows are changing what's deployable on-premise. That matters more than ever for healthcare AI.]]></content:encoded>
            <author>clint@1putthealth.com (Clint Johnson)</author>
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            <title><![CDATA[From GPT-2 to DeepSeek: The Architectural Changes That Actually Mattered]]></title>
            <link>https://www.clint-johnson.com/articles/llm-architecture-evolution</link>
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            <pubDate>Tue, 04 Feb 2025 00:00:00 GMT</pubDate>
            <description><![CDATA[I've been reading ML papers for 10 years. Most don't matter. These architectural choices did. RoPE, GQA, SwiGLU: each one solved a real scaling problem. What to look for when a new model claims 'better architecture.']]></description>
            <content:encoded><![CDATA[I've been reading ML papers for 10 years. Most don't matter. These architectural choices did. RoPE, GQA, SwiGLU: each one solved a real scaling problem. What to look for when a new model claims 'better architecture.']]></content:encoded>
            <author>clint@1putthealth.com (Clint Johnson)</author>
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