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    Nvidia Notifies Customers of AI Server Price Increases

    Posts reference Bloomberg report on memory costs driving server price changes next year.

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    7 Sources, 39d ago, first seen 39d ago

    TLDR

    Posts reference a Bloomberg report stating Nvidia has notified key customers that prices for servers equipped with its artificial intelligence chips will increase, driven by higher memory chip expenses. These changes apply to shipments beginning early next year. Social media discussions connect the adjustments to wider cost pressures including those on accelerators and labor. Mentions of an upgrade to Verra Rubin appear alongside notes that the per gigawatt cost estimates are rising. Server makers reportedly indicate price increases for leading AI accelerators.

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    235.9K

    7 Sources, first seen 39d ago

    Combined views

    235.9K

    7 Sources, first seen 39d ago

    1.7K likes
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    1.7K likes
    102 comments
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    76 reposts

    Sentiment

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    102 comments
    214 saves
    76 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

    7 Sources

    @firstadopterBloomberg: "Some of Nvidia Corp.’s biggest customers have been told that the prices of servers containing its artificial intelligence chips are going up more than 15% in many cases with memory chip costs soaring. The price hikes will go into effect on systems shipped early next year and will impact systems including those with the flagship Vera Rubin and Grace Blackwell chips"
    @rohanpaul_aiJUST IN: Nvidia has informed some of its major customers that servers powered by its AI chips are getting ~17% pricier in many cases. Memory inflation is pushing the prices of Nvidia’s Grace Blackwell and Vera Rubin systems sharply higher. Memory is the pressure point because NVIDIA Vera Rubin NVL72 packs 20.7TB of HBM4 and 54TB of LPDDR5X in each rack. TrendForce expects DRAM supply to remain tight through 2027, as AI servers keep pulling production toward HBM and server memory. A 17% Nvidia server-price increase could add at least $5B to 1GW builds. That extra $5B arrives before operators pay for the rest of the data center, including power, cooling, networking, buildings, and financing. Cloud providers can absorb some of the increase, but passing it through would raise the cost of renting Nvidia compute for training and inference. Nvidia's recent land-and-power investments look more consequential once each delayed rack is worth more. Nvidia has invested in Cloverleaf and SB Energy, both tied to securing sites and power for AI data centers. A delivered GPU produces no revenue if the data center lacks power or a finished shell. When memory inflation raises the capital tied up in each deployment, customers have more money sitting idle during delays. Nvidia therefore has a financial reason to secure site readiness itself, reducing the chance that infrastructure delays push expensive hardware orders into later periods.
    @ShanuMathew93Between the upgrade to Verra Rubin, price hikes in accelerators, memory, labor, eg. That $50bn per GW figure is increasingly moving to $60bn+
    @DanielleFongRT @ShanuMathew93: Between the upgrade to Verra Rubin, price hikes in accelerators, memory, labor, eg. That $50bn per GW figure is increasi…
    @zephyr_z9GB300 used to cost around $4M 2x the cost for 2x-3x more tokens per server
    @GavinSBakerThe most obvious implication of GPU price increase is that anyone who is spending a lot on Blackwell and Rubin before January 31, 2027 is in a good relative position vs. competitors. Super curious to know if GPU prices are going up more than rack prices.

    7 Sources

    @firstadopterBloomberg: "Some of Nvidia Corp.’s biggest customers have been told that the prices of servers containing its artificial intelligence chips are going up more than 15% in many cases with memory chip costs soaring. The price hikes will go into effect on systems shipped early next year and will impact systems including those with the flagship Vera Rubin and Grace Blackwell chips"
    @rohanpaul_aiJUST IN: Nvidia has informed some of its major customers that servers powered by its AI chips are getting ~17% pricier in many cases. Memory inflation is pushing the prices of Nvidia’s Grace Blackwell and Vera Rubin systems sharply higher. Memory is the pressure point because NVIDIA Vera Rubin NVL72 packs 20.7TB of HBM4 and 54TB of LPDDR5X in each rack. TrendForce expects DRAM supply to remain tight through 2027, as AI servers keep pulling production toward HBM and server memory. A 17% Nvidia server-price increase could add at least $5B to 1GW builds. That extra $5B arrives before operators pay for the rest of the data center, including power, cooling, networking, buildings, and financing. Cloud providers can absorb some of the increase, but passing it through would raise the cost of renting Nvidia compute for training and inference. Nvidia's recent land-and-power investments look more consequential once each delayed rack is worth more. Nvidia has invested in Cloverleaf and SB Energy, both tied to securing sites and power for AI data centers. A delivered GPU produces no revenue if the data center lacks power or a finished shell. When memory inflation raises the capital tied up in each deployment, customers have more money sitting idle during delays. Nvidia therefore has a financial reason to secure site readiness itself, reducing the chance that infrastructure delays push expensive hardware orders into later periods.
    @ShanuMathew93Between the upgrade to Verra Rubin, price hikes in accelerators, memory, labor, eg. That $50bn per GW figure is increasingly moving to $60bn+
    @DanielleFongRT @ShanuMathew93: Between the upgrade to Verra Rubin, price hikes in accelerators, memory, labor, eg. That $50bn per GW figure is increasi…
    @zephyr_z9GB300 used to cost around $4M 2x the cost for 2x-3x more tokens per server
    @GavinSBakerThe most obvious implication of GPU price increase is that anyone who is spending a lot on Blackwell and Rubin before January 31, 2027 is in a good relative position vs. competitors. Super curious to know if GPU prices are going up more than rack prices.