Noah Berger/Getty Images via Amazon Web Services
- AWS is raising key AI cloud prices by 20%, after a 15% price increase in January.
- Soaring memory chip costs and strong AI demand is driving higher pricing for cloud customers.
- Memory shortages have sent Micron and SK Hynix surging to records.
Amazon raised prices for several key AI cloud offerings, the latest sign that memory chip shortages are driving up the cost of some technology.
Amazon Web Services recently announced price increases for EC2 Capacity Blocks for ML. This is a cloud service that lets companies reserve GPUs in advance.
The changes mean hourly rates for renting several types of cloud servers will jump by roughly 20% starting in July. AWS had already raised prices for the same service by about 15% in January.
"Amazon EC2 Capacity Blocks for ML reservation prices are updated periodically based on supply and demand," the company said in its announcement. Amazon didn't immediately respond to a request for comment on Friday.
Similar price increases are happening in other parts of the tech industry, as tech giants pass memory price pressure on to customers. Apple raised prices this week, blaming soaring memory chip costs. Xbox did the same, and Elon Musk complained about unprecedented memory price increases.
The AWS move is more consequential than your next MacBook or gaming console costing a couple of hundred dollars more. As the world's largest cloud provider, AWS underpins many software services, and millions of developers rely on the cloud service to offer apps and other tech products. Price increases of 15% and now 20% will likely ripple through these sectors in coming quarters.
The price hikes reflect a broader shift in tech: AI is increasingly constrained by physical limitations, rather than software availability. Tight memory chip supply and strong GPU demand are raising costs for cloud providers.
One of the biggest physical constraints right now is high-bandwidth memory, a critical component packaged alongside advanced AI chips. AI cloud services run on these chips and servers, so shortages and price increases like this have a big impact on data center expansion plans and, ultimately, the supply of AI.
"As there is a limit to how much memory can be produced, then there is a limit to how many GPUs can be produced, which means that there's a limit to how many data centers can be built," Peter Berezin, chief economist at BCA Research, wrote on X on Friday.
Berezin added that cloud providers can pass on higher infrastructure costs because customers have few alternatives when GPU capacity is scarce, giving hyperscalers AWS, Microsoft, Google, and Oracle greater pricing power.
"While the memory shortage raises their costs, it also keeps the demand for compute above the available supply, which gives them greater pricing power over access to cloud computing," Berezin wrote on X.
The same shortages pushing up AI cloud prices have propelled memory-chip makers such as Micron and SK Hynix to records, reflecting investor expectations that AI-driven demand will keep the market tight, and prices high, for years.
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