Nvidia (NASDAQ:NVDA) shares took a sharp hit during Monday’s session, falling as part of a broader selloff in AI stocks. The stock plunged ~17%, marking its steepest single-day percentage drop since March 2020. What’s more, Nvidia saw its market cap shrink by roughly $590 billion, the largest single-day value drop ever recorded.
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The selloff was triggered by the entry of Chinese AI start-up DeepSeek, which introduced a large-language model viewed as a serious contender to OpenAI and Meta Platforms. In late December, DeepSeek unveiled a free, open-source language model, developed in just two months for under $6 million—a fraction of the investment made by its Western rivals. More recently, the company introduced a reasoning model that, according to reports, outperformed OpenAI’s latest in multiple third-party evaluations.
But why was Nvidia hit so hard? The answer lies in the implications for its core business: DeepSeek’s ability to develop advanced AI models at a fraction of the cost suggests that companies may no longer need to invest heavily in Nvidia’s expensive GPUs to achieve similar breakthroughs.
However, such fears of “peak spending on GPUs” are completely misplaced, says Cantor analyst C.J. Muse, who ranks among the top 2% of Wall Street stock pros.
“We think this view is farthest from the truth and that the announcement is actually very bullish with AGI (artificial general intelligence) seemingly closer to reality and Jevons Paradox (what happens when improved efficiency actually boosts demand, causing resources to be used up more quickly overall) almost certainly leading to the AI industry wanting more compute, not less,” said Muse.
Muse thinks DeepSeek’s success underscores the “great efficiency” of open-source models, like those built on PyTorch and Llama. However, the analyst has some doubts about the claim that this model only costs $5.57 million compared to LLAMA 3.1’s $500 million. Additionally, some reports suggest DeepSeek may be using 50k Hopper GPUs instead of the stated 10k A100s, which is odd, given the “GPU embargo.” Lastly, Muse notes it’s clear DeepSeek has made “interesting leaps” in optimizing training methods, which has led to better performance vs. other LLMs.
Ultimately, Muse believes DeepSeek’s progress brings us closer to AGI. Progress will continue to be made in areas like pre-training in areas like pre-training, post-training, and time-based inference/reasoning, and future investments in large-scale clusters will speed up. “All of which is bullish for AI,” says Muse.
All this innovation is lowering the cost of adoption and making AI more widespread, thereby supporting Jevons Paradox. “We see this progress as a sign that the demand for more compute will keep growing over time, not shrinking,” the analyst summed up.
As such, Muse’s advice for investors is to scoop up shares on the weakness. He assigns an Overweight (i.e., Buy) rating to NVDA stock, with a price target of $200 – implying a potential 69% upside over the next 12 months. (See NVDA stock forecast)
Most of Muse’s colleagues agree with his stance; based on a mix of 36 Buys vs. 3 Holds, the consensus view is that NVDA is a Strong Buy. The average price target stands at $177.56, implying shares will gain ~50% over the coming year. (See Nvidia stock forecast)
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Disclaimer: The opinions expressed in this article are solely those of the featured analyst. The content is intended to be used for informational purposes only. It is very important to do your own analysis before making any investment.