BEIJING, Nov 19 (Reuters) - Nvidia's ( NVDA ) move to

use smartphone-style memory chips in its artificial intelligence

servers could cause server-memory prices to double by late 2026,

according to a report published on Wednesday by Counterpoint

Research.

In the past two months, electronics supply chains around the

world have been hit by a shortage of legacy memory chips as

manufacturers turned their focus to high-end memory chips suited

to semiconductors designed for AI applications.

But Counterpoint, a technology-focused market research firm,

said there was a new problem on the horizon. Nvidia ( NVDA ) recently

decided to reduce AI server power costs by changing the kind of

memory chip it uses to LPDDR, a type of low-power memory chip

normally found in phones and tablets, from DDR5 chips, which are

typically used in servers.

Because each AI server needs more memory chips than a

handset, the change is expected to create sudden demand that the

industry is not equipped to handle, according to Counterpoint.

Nvidia ( NVDA ) is scheduled to release its earnings report later on

Wednesday.

Memory suppliers like Samsung Electronics ( SSNLF ), SK

Hynix and Micron are already facing shortages

of older dynamic random-access memory products after reducing

production to focus on high-bandwidth memory, which is necessary

to make the advanced accelerators that power the global AI boom.

Counterpoint said tightness at the low end of the market was

at risk of spreading upward as chipmakers weigh whether to

divert more factory capacity to LPDDR to meet Nvidia's ( NVDA ) needs.

"The bigger risk on the horizon is with advanced memory, as

Nvidia's ( NVDA ) recent pivot to LPDDR means they're a customer on the

scale of a major smartphone maker - a seismic shift for the

supply chain which can't easily absorb this scale of demand,"

Counterpoint said.

The firm said it expected prices for server-memory chips to

double by the end of 2026. It also forecast that overall memory

chip prices were likely to rise 50% from current levels through

the second quarter of 2026.

Higher server-memory prices would raise costs for cloud

providers and AI developers, potentially adding pressure to

data-centre budgets that are already stretched by record

spending on graphics processing units and power upgrades.