Investing.com- Shares of artificial intelligence darling Nvidia fell on Friday after the launch of Chinese generative AI program Deepseek last week, which it claimed could outperform rival offerings at a fraction of their costs.
Nvidia Corporation (NASDAQ: ) shares fell more than 3% to $142.62 on Friday, although they still finished higher for the week.
DeepSeek—funded by a high-flyer Chinese quantum company—open-sourced its R1 LLM and also published a paper showing how advanced LLMs can be built on much smaller budgets.
Deepseek had access to about 50,000 NVIDIA H100 AI GPUs – the previous generation of NVIDIA’s AI GPUs, which are supposed to replace the Blackwell Series. It was unclear to what extent the company took this approach for its LLM.
But the biggest point of contention over Deepseek R1 was that LLM was able to achieve competitive results despite its rivals, such as OpenAi’s Chatgpt and Meta Lam, with access to significantly larger budgets and more advanced technology. This term was relevant in light of recent US export controls on CHIP technology in China, as well as US President Donald Trump announcing $500 billion in private spending to build more US AI infrastructure.
DeepSeek R1 raised questions about how justified the billions in capital expenditures undertaken by Wall Street tech giants were to advance AI.
Of the so-called Magnificent 7 stocks, Microsoft (NASDAQ 🙂 , Meta (NASDAQ 🙂 ) and Apcebet (NASDAQ 🙂 have all announced rapid increases in capital spending in recent quarters to advance their AI ambitions. Analysts expect that to remain the case when they report December earnings this week.
“That could be good news for MAG-7, which can learn from Deepseek to design AI systems with a cheaper GPU. This would reduce their capital expenditure and increase their profits. This may not be a happy development for Nvidia,” Yardeni Research said in a note.
Nvidia has benefited greatly from increased investment in AI over the past two years, seeing exponential sales growth as the tech giants sought to boost their AI development by increasing their data center capabilities.
But DeepSeek’s success raises questions about whether AI developers can make progress by building leaner, more efficient models that don’t require as much investment in chip technology.
JPMorgan’s Joshua Meyers said concerns about higher AI budgets were “overblown,” noting that Deepseek’s efficiency may have been needed, given that Chinese companies are blocked from accessing advanced U.S. chip technology.
“If DeepSeek can lower inference costs, then others will have to, and demand will hopefully more than make up for it over time,” Meyers wrote in a brief note on Saturday.
