Nvidia is aggressively securing high-bandwidth memory supply from SK Hynix as part of a $500 billion AI deal, according to CNBC, tying up a component the outlet describes as essential to Nvidia's GPUs and systems.
Key facts
- CNBC reported that Nvidia is locking down memory supply from SK Hynix.
- The move is described as part of a $500 billion AI deal.
- CNBC says high-bandwidth memory is an essential component for Nvidia's GPUs and systems.
- The report was published by CNBC on 25 July 2026.
- The full breakdown of the $500 billion figure and further deal terms were not detailed in the available reporting.
Nvidia is moving to secure its supply of high-bandwidth memory from SK Hynix as part of a $500 billion artificial intelligence deal, according to CNBC. The outlet reported that Nvidia is acting aggressively to secure this supply.
CNBC described high-bandwidth memory as an essential component for Nvidia’s graphics processing units and systems.
The available reporting did not detail the full breakdown of how the $500 billion figure is allocated, the specific terms of the SK Hynix arrangement, or a timeline. SK Hynix’s and Nvidia’s own statements on the deal were not included in the source reviewed.
Honest Abe News based this report on a single CNBC account and will update the story as further details are confirmed.
Why it matters
Memory components have become central to Nvidia's expanding AI hardware business, and CNBC's report indicates the company is moving to lock in supply from a major memory maker. Further details of the arrangement's scope and impact are not yet available.
Frequently asked questions
What is Nvidia securing from SK Hynix?
According to CNBC, Nvidia is securing supply of high-bandwidth memory, an essential component for its GPUs and systems, from SK Hynix.
How large is the AI deal involved?
CNBC reported the memory arrangement is part of a $500 billion AI deal.
Why is high-bandwidth memory important?
CNBC describes high-bandwidth memory as an essential component for Nvidia's GPUs and systems, making it critical to producing advanced AI hardware.