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Nvidia Stock Investors Just Got Bad News From DeepSeek, but Certain Wall Street Analysts See a Silver Lining

Nvidia (NASDAQ: NVDA) made stock market history on Monday, Jan. 27, but not the good kind. The chipmaker saw its share price decline 17%, due to concerns about an artificial intelligence (AI) model from Chinese start-up DeepSeek. That nosedive erased $589 billion of its market value, the largest single-day loss for any company on record.

What triggered the meltdown? Despite regulations from the U.S. government that prohibit Nvidia from exporting its most advanced AI chips to China, DeepSeek reportedly created a large language model that rivals the performance of the more sophisticated models created in the U.S. The company also claims it trained the model while spending much less money and without the most advanced Nvidia chips.

That news has been disastrous for Nvidia shareholders, given how sharply the stock crashed. But many Wall Street analysts see the sell-off as an overreaction that creates a long-awaited buying opportunity for investors.

DeepSeek published a research paper last week claiming its R1 reasoning model rivals the performance of OpenAI’s o1 problem-solving model on certain benchmarks. The Chinese start-up also claims it spent less than $6 million training the large language model and says it completed the training with only 2,048 Nvidia H800 graphics processing units (GPUs). Importantly, the H800 GPU was designed specifically to comply with export restrictions.

Comparatively, OpenAI spent more than $100 million training its GPT-4 model and used the more powerful Nvidia H100 GPUs. The company hasn’t disclosed the precise number, but analysts estimate OpenAI used over 10,000 processors to train GPT-4. That estimate is plausible, given that Meta Platforms used 16,000 Nvidia H100 GPUs to train its Llama 3 model, spending an estimated $60 million.

The implications are alarming for Nvidia. If DeepSeek trained R1 using fewer, less-powerful chips, then U.S. companies could theoretically reduce spending by mimicking the training techniques employed by the Chinese AI start-up. In turn, hyperscale companies like Amazon, Alphabet, Meta Platforms, and Microsoft could spend less than previously anticipated on Nvidia GPUs in the coming years.

Image source: Getty Images.

While DeepSeek trained its R1 model with impressive efficiency, many analysts view that as a positive development. They think it will accelerate the pace at which artificial intelligence is adopted, driving greater demand for Nvidia GPUs. Also, some industry experts question the validity of DeepSeek’s claims concerning costs and infrastructure.


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