Investing.com — Rising memory chip costs are pushing up the price of servers that use ’s artificial intelligence chips, with some of the chipmaker’s biggest customers facing increases of more than 15%, Bloomberg News reported on Saturday, citing people familiar with the matter.
The higher prices are expected to apply to systems shipped early next year, including those equipped with Nvidia’s flagship Vera Rubin and Grace Blackwell chips, the report said.
The size of the increase will vary depending on the Nvidia chip generation and memory configuration.
Companies that build servers under contract for major data center operators such as , Alphabet Inc’s Google and have recently notified customers of the upcoming price increases, the report said, citing sources who asked not to be identified because the communications have not yet been made public.
Memory chipmakers , and have gained unprecedented leverage amid a surge in demand for AI infrastructure, with the two Korean firms and Micron accounting for most of the world’s DRAM production, the report said.
The effectiveness of Nvidia’s AI accelerator processors depends on how much DRAM they are paired with, the report said.
Major technology companies including and Qualcomm Inc have recently said they have been forced to raise prices because of chip shortages.
Nvidia has a gross margin of 75%, which said the chipmaker can charge tens of thousands of dollars per chip because supply from contract manufacturer still cannot meet runaway demand.
Nvidia has also raised prices for its gaming-oriented PC graphics cards, the report said, citing industry news site Tom’s Hardware.
Major customers including , Microsoft, Google and are all pursuing their own in-house chip programs but remain dependent on purchases from Nvidia for their data center build-outs, according to the report.
Their ability to gain greater independence will also hinge on access to supply from Samsung, SK Hynix and Micron, the report added.
The price increases are also likely to add complexity to the industry’s massive AI data center build-out ambitions, the report added, noting that project delays, labor shortages, tightening capital markets and community resistance to developments have already complicated many plans.