Investing.com - Shares in artificial intelligence-darling Nvidia (NASDAQ: NVDA ) tumbled by more than 12% in early US trading on Monday, erasing $465 billion in market value and weighing on the tech-heavy Nasdaq Composite , as a new model from Chinese start-up DeepSeek cast doubt over heavy recent investments in AI infrastructure.
At 09:33 EST (14:33 GMT), Nvidia shares had fallen by 10.8%, placing the stock potentially on track for its worst single day move since near the beginning of the COVID-19 crisis in March 2020.
"For investors holding Nvidia or related stocks, the critical question is whether [capital expenditure] growth in 2026 can maintain its trajectory, especially in a market priced for perfection," US Tiger Research analysts wrote in a client note.
"Until there’s clarity, Nvidia’s increased uncertainty will pressure its stock price."
Broader Wall Street indices also fell sharply, after DeepSeek launched a set of open-source models over the past week claiming to match offerings from rivals such as OpenAI's ChatGPT in performance for a fraction of the cost.
The release and testing of the company’s flagship model -- DeepSeek R1 -- sparked questions over a surge in spending on building out AI infrastructure by major US tech companies.
Bernstein analysts noted that the new models were impressive, especially in their ability to compete with similar products from OpenAI and Meta Platforms (NASDAQ: META ). However, they said the broader market reaction to DeepSeek's models appears to be overblown.
“If we acknowledge that DeepSeek may have reduced costs of achieving equivalent model performance by, say, 10 [times], we also note that current model cost trajectories are increasing by about that much every year anyway [...] which can’t continue forever,” Bernstein analysts wrote in a note.
They added that the AI industry needed innovations like DeepSeek to keep progressing, because it could help squeeze more out of existing hardware.
The brokerage noted that the need for increased AI infrastructure remains, saying that any fresh computing capacity was likely to get absorbed by a jump in AI demand.
(Ambar Warrick and Senad Karaahmetovic contributed reporting.)