*

Top US AI labs analyze DeepSeek's low-cost models

*

Snowflake adds DeepSeek models amid customer demand

*

DeepSeek likely spent more than widely reported $6 million

figure, experts say

By Kenrick Cai, Anna Tong and Jeffrey Dastin

SAN FRANCISCO, Jan 28 - Developers at leading U.S. AI

firms are praising the DeepSeek AI models that have leapt into

prominence while also trying to poke holes in the notion that

their multi-billion dollar technology has been bested by a

Chinese newcomer's low-cost alternative.

Chinese startup DeepSeek on Monday sparked a stock selloff

and its free AI assistant overtook OpenAI's ChatGPT atop Apple's ( AAPL )

App Store in the U.S., harnessing a model it said it

trained on Nvidia's ( NVDA ) lower-capability H800 processor

chips using under $6 million.

As worries about competition reverberated across the

U.S. stock market, some AI experts applauded DeepSeek's strong

team and up-to-date research but remained unfazed by the

development, said people familiar with the thinking at four of

the leading AI labs, who declined to be identified as they were

not authorized to speak on the record.

OpenAI CEO Sam Altman wrote on X that R1, one of several

models DeepSeek released in recent weeks, "is an impressive

model, particularly around what they're able to deliver for the

price." Nvidia ( NVDA ) said in a statement DeepSeek's achievement proved

the need for more of its chips.

Software maker Snowflake decided Monday to add

DeepSeek models to its AI model marketplace after receiving a

flurry of customer inquiries.

With employees also calling DeepSeek's models "amazing," the

U.S. software seller weighed the potential risks of hosting AI

technology developed in China before ultimately deciding to

offer it to clients, said Christian Kleinerman, Snowflake's

executive vice president of product.

"We decided that as long as we are clear to customers, we

see no issues supporting it," he said.

Meanwhile, U.S. AI developers are hurrying to analyze

DeepSeek's V3 model. DeepSeek in December published a research

paper accompanying the model, the basis of its popular app, but

many questions such as total development costs are not answered

in the document.

China has now leapfrogged from 18 months to six months

behind state-of-the-art AI models developed in the U.S., one

person said. Yet with DeepSeek's free release strategy drumming

up such excitement, the firm may soon find itself without enough

chips to meet demand, this person predicted.

DeepSeek's strides did not flow solely from a $6 million

shoestring budget, a tiny sum compared to $250 billion analysts

estimate big U.S. cloud companies will spend this year on AI

infrastructure. The research paper noted that this cost referred

specifically to chip usage on its final training run, not the

entire cost of development.

The training run is the tip of the iceberg in terms of total

cost, executives at two top labs told Reuters. The cost to

determine how to design that training run can cost magnitudes

more money, they said.

The paper stated that the training run for V3 was conducted

using 2,048 of Nvidia's ( NVDA ) H800 chips, which were designed to

comply with U.S. export controls released in 2022, rules that

experts told Reuters would barely slow China's AI progress.

Sources at two AI labs said they expected earlier stages of

development to have relied on a much larger quantity of chips.

One of the people said such an investment could have cost north

of $1 billion.

Some American AI leaders lauded DeepSeek's decision to

launch its models as open source, which means other companies or

individuals are free to use or change them.

"DeepSeek R1 is one of the most amazing and impressive

breakthroughs I've ever seen - and as open source, a profound

gift to the world," venture capitalist Marc Andreessen said in a

post on X on Sunday.

The acclaim garnered by DeepSeek's models underscores the

viability of open source AI technology as an alternative to

costly and tightly controlled technology such as OpenAI's

ChatGPT, industry watchers said.

Wall Street's most valuable companies have surged in recent

years on expectations that only they had access to the vast

capital and computing power necessary to develop and scale

emerging AI technology. Those assumptions will come under

further scrutiny this week and the next, when many American tech

giants will report quarterly earnings.