No one thought the path to artificial general intelligence (AGI) would be smooth for investors, but the emergence of DeepSeek has clearly thrown a plot twist into the AI narrative.
Nvidia (NVDA -3.67%) and other AI stocks plunged on Monday, Jan. 27, as investors responded to the threat from DeepSeek, the Chinese AI chatbot that rivals top models like ChatGPT for a fraction of the cost.
Nvidia lost 17% in one session, wiping out $600 billion in market value, the biggest one-day loss for a single stock in market history. Since then, Nvidia has recouped some of those losses, a sign investors may believe the sell-off may have been an overreaction.
Nonetheless, AI stocks remain significantly lower, and Nvidia itself tipped its hat to the Chinese start-up, with a spokesperson calling it “an excellent AI advancement.”
DeepSeek also seems to be gaining credibility, as Microsoft, which is believed to be OpenAI’s biggest investor, has already added the model to its Azure cloud infrastructure service.
So how big of a threat is DeepSeek to the AI ecosystem? To answer that question, let’s outline a few facts about DeepSeek first.
Image source: Nvidia.
What we know about DeepSeek
DeepSeek is a Chinese AI start-up founded by hedge fund chief Liang Wenfeng in May 2023. Unlike OpenAI’s ChatGPT or Alphabet‘s Gemini, DeepSeek uses an open-source large language model, meaning developers can update it and adapt it to their own needs.
DeepSeek is significant because its R1 model rivals OpenAI’s o1 in categories like math, code, and reasoning tasks, and it purportedly does that with less advanced chips and at a much lower cost.
According to one estimate, it costs OpenAI’s o1 model $60 to generate a million tokens of output, while DeepSeek’s R1 can deliver the same quantity for just $2.19.
DeepSeek has impressed industry insiders with a 22-page research paper explaining how its model works, but the company has also been accused by OpenAI of using a method called distillation to build its models, a cost-efficient way of training an AI model using larger, more adept ones. Doing so constitutes a violation of OpenAI’s terms of service.
Distillation is commonly used in AI, but if that accusation is true, it would seem to undermine a lot of DeepSeek’s credibility, making it seem like the Chinese start-up plagiarized at least part of its model.
There’s also a debate over how much DeepSeek actually paid for its infrastructure, as it said it cost just $5.6 million to train its V3 model. The V3 was built on Nvidia H800s, which were made to get around U.S. export rules and perform similarly to H100s, Nvidia’s GPUs that have been widely used to build AI infrastructure and models in the U.S.
Analysts have cast doubt on the $5.6 million figure, and that doesn’t seem to include essential costs like research, architecture, or data, making it difficult to do a direct comparison with U.S-based AI models that have required billions of dollars in investments.
What it means for Nvidia
It’s too early to know what the implications of DeepSeek are for Nvidia and the broader AI sector, and there’s still a lot of uncertainty around what exactly DeepSeek has achieved.
The company appears to have made genuine gains in efficiency, but those seem less impressive if its model was built in part by borrowing from OpenAI. The true cost of the model also isn’t fully clear.
The DeepSeek-R1 launch was called a “Sputnik moment” by Silicon Valley honcho Marc Andreessen and others, and the geopolitical implications of the new chatbot could be just as meaningful as the technological ones.
The U.S. could respond by intensifying the tech cold war with China, tightening export rules further and taking other measures. Additionally, allowing DeepSeek on U.S. smartphones while banning TikTok seems incongruous, and U.S. corporations and governments are likely to be skeptical of handing their data over to a Chinese start-up.
For Nvidia investors, it’s also worth remembering that this is just one episode in a years-long technology evolution, and is probably not as meaningful as a $600 billion one-day sell-off makes it seem. Even if DeepSeek shifts the entire industry to a more efficient open-source architecture, that could be a positive for Nvidia over the long run. According to Jevons paradox, lowering the price to run AI models could increase demand, leading to an increase in total consumption, which would drive more purchases of AI chips from Nvidia, though likely at a lower cost.
It’s also meaningful that DeepSeek was built on Nvidia chips. No one’s challenging its supremacy there.
Why I’m not worried about Nvidia
Investors shouldn’t miss the forest for the trees here. You should remember that a competent AI chatbot isn’t the goal here. The ultimate goal is artificial general intelligence, including applications like autonomous vehicles and robotics, and it’s unclear if DeepSeek dramatically changes the calculus around that.
Those technologies are powerful and valuable enough that the race toward AGI will continue, and the tech giants competing in it will continue to pour billions into the infrastructure necessary to build it. Efficiency is important, but technological leadership is the real prize here.
Nvidia stock was already dealt a setback by DeepSeek, and that could be true of Nvidia’s business as well, but the company has proven itself to be nimble before.
It’s evolved its technology to go from primarily serving video games to cryptocurrency mining, AI, autonomous vehicles, 3D rendering, and more. CEO Jensen Huang is rightly regarded as a visionary in the industry, and it continues to rapidly innovate with its new Rubin platform in development.
The AI frontier will continue to evolve, and Nvidia will adapt to market conditions as needed. Whatever the impact of DeepSeek, the race to AGI isn’t going away, and neither is Nvidia.
