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Nvidia halves the memory planned behind each Vera CPU

JPMorgan calls the cut content optimization as a coping mechanism for tight supply. For anyone budgeting a refresh, the working assumption flips to less capability per dollar in the out-years.

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Photograph accompanying Nvidia halves the memory planned behind each Vera CPU
Photo: wccftech.com

What happened

  • JPMorgan says Nvidia has halved the SOCAMM memory planned for each Vera CPU, taking it from 1.5TB down to 768GB.
  • Omdia senior analyst Runar Bjorhovde says memory components now cost four or five times what they did around a year ago.
  • CCS Insight analyst Ben Hatton says brands are returning to 4G phone designs because they can use less memory than an equivalent 5G device.

Why it matters

  • constraint Published per-socket memory is now a ceiling that can be halved before the part ships, so headroom assumptions in a cluster sizing model have to carry a discount the vendor has not named.
  • cost Below $500 there is no margin to absorb component inflation, so the buyer pays in capability rather than price, and the fleet ends up slower than the one it replaced.
  • decision Refresh timing becomes the live call: order at today's configuration and pay, or defer into parts shaped by allocation, with relief bounded only loosely by an 18-month price view and a mid-2028 squeeze estimate.
  • contradiction A shipped spec that shrinks would normally read as demand easing, and JPMorgan says it is the reverse, which means procurement models inferring requirement from configuration are reading supply, not workload.

Put last year's Vera figure next to this year's and the cut divides too cleanly to be a design refinement. The planned 1.5TB per CPU is 1536GB in binary terms, and the new number, 768GB, is exactly half of it [1][14]. The Rubin Ultra change has the same shape: going from 16-high HBM4E stacks to 12-high or 8-high removes a quarter or a half of the dies in a stack [2][15]. JPMorgan's phrase for this is content optimization as a coping mechanism, and the bank is explicit that the systems did not suddenly need less memory [7].

The same allocation runs down the price list. Omdia's Runar Bjorhovde puts memory components at four or five times their cost of about a year ago [3], and says memory can now be more than half the bill of materials in some cheaper devices, against 10% to 15% before the spike [8]. That is roughly a threefold to fivefold rise in the share of a device that one component eats [17]. A budget handset has nowhere to put that, so the answer is a 4G radio, which CCS Insight's Ben Hatton says gets away with less memory than an equivalent 5G design [4], alongside reduced storage and older Qualcomm or MediaTek parts [5]. Hatton's read on the sub-$500 tier is that buyers will get a less powerful product [10]. New capacity does not arrive inside the planning window either: plants take two to three years to build, and are increasingly specified for higher-return GPUs rather than basic components [9].

Here is what users actually do while that plays out. Samsung's biggest seller by volume in Europe is the Galaxy A16 4G, a cheap model already around 18 months old, according to Bjorhovde [11]. Xiaomi shipped about 25% fewer units year over year in the first half of 2026 while revenue fell only about 5% [6], which works out to roughly 27% more revenue per unit sold [16].

Here is what hardware plans tell themselves: that a part a generation out is a superset of the one you can order today, so capacity per socket is a floor you build on. What the Vera and Rubin Ultra revisions show is capacity per socket being set by what the supplier can obtain [7]. The forcing function for anyone with a 2027 refresh in a spreadsheet is two questions per line item. First, is the capacity number in a configuration you can order and take delivery of, or in a slide. Second, if the shipped part lands at half the planned memory, does the workload fail or does it just run slower. A slide number attached to a workload that fails is the cell to re-plan this quarter. An orderable number attached to a workload that fails means buying earlier than you wanted. Everything that merely runs slower can wait and absorb the cut.

Neither analyst gives a date when a spec sheet becomes a reliable input again, and they are not measuring the same clock: Bjorhovde doubts meaningful price declines within 18 months, while Hatton expects the squeeze to last until at least mid-2028 [18]. Bjorhovde's own framing is that at this scale he has not seen anything like it before [13]. For the person defending a fleet or cluster budget on Friday, the usable version is to write the out-year plan with less capability per dollar and book any restored spec as upside.

What to watch

  • Whether shipped Vera and Rubin Ultra configurations match the reduced SOCAMM and stack-height numbers JPMorgan describes, or get quietly restored.
  • Whether Apple's September lineup, expected to include the iPhone 18 Pro and a first foldable, moves storage and memory tiers rather than headline prices.
  • Whether any major memory maker commits new capacity to commodity parts instead of the high-end products hyperscalers are paying up for.

Clarity's read

What the record supports and how the coverage leans. The claims behind it follow.

Reality

Evidence40
Adoption58
Hype gap+18
Incentives62
Confidence45
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  1. [1]

    JPMorgan says Nvidia has halved the planned amount of SOCAMM memory attached to each Vera CPU, from 1.5TB to 768GB.

    ReportedSupportedSource: JPMorgan, via Fast Company2 sources— create a free account to open themView cited source
  2. [2]

    Nvidia has reduced the planned HBM memory in its Rubin Ultra systems, moving from 16-high HBM4E stacks to 8-high or 12-high versions.

    ReportedSupportedSource: JPMorgan, via Fast Company2 sources— create a free account to open themView cited source
  3. [3]

    Runar Bjorhovde, senior analyst at Omdia, says memory components now cost four or five times what they did a year or so ago.

    ReportedSupportedSource: Runar Bjorhovde, Omdia2 sources— create a free account to open themView cited source

Sources

1 independent publisher whose own reporting we read for this story.

  1. fastcompany.com

    1 article · August 27, 2026

    AI is making your gadgets more expensive and less powerful

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