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Every new NVIDIA generation ships into the same problem: Hyperscalers get the first allocation, everyone else waits. Vera Rubin NVL72 is no different, and this time the numbers behind it are bigger than ever🧵

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Aethir

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17,439 views • 1 month ago •via X (Twitter)

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The first-ever measured silicon numbers for @NVIDIA Vera Rubin NVL72 are in 😲 First measured performance shows 10x more tokens per megawatt than Blackwell. No projections. Real results from live hardware.
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The first-ever measured silicon numbers for @NVIDIA Vera Rubin NVL72 are in 😲 First measured performance shows 10x more tokens per megawatt than Blackwell. No projections. Real results from live hardware.

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Jensen announced on stage at #COMPUTEX2026 that we'll be among the first cloud providers to bring up NVIDIA Vera Rubin NVL72, to help accelerate the era of AI factories. As part of NVIDIA's full-stack AI factory platform, Vera Rubin NVL72 is designed to run frontier and open-source models with exceptional performance, efficiency, and scalability—delivering more intelligence per watt and lower token costs at scale. It's GO time. ⚡️

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Google engineers are running 3 NVIDIA DGX Spark boxes each just to speed up their Claude skills workflows by 300% > and the gap between them and everyone else is getting wider every week $95K developer vs $300K AI architect. same job. different stack > /self-improving-agent - the system improves its own process without you touching it > /rag-architect - retrieval quality now matters more than raw model cleverness > /connect-apps - Claude takes real actions across Gmail, Slack, GitHub and Notion the people who build this stack now will be the $300K architects everyone asks "what's your setup?" > everyone else will still be typing prompts full list with GitHub links in the article above 👇

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