Is Nvidia (NVDA) Really Doomed? Here’s Why We Don’t Think So

The AI landscape is shifting rapidly, and DeepSeek’s announcement of its R1 large language model (LLM) has added fuel to the fire. Nvidia (NVDA) stock dropped more than 13% pre-market and the Nasdaq 100 fell 4% as investors grabbled with the implications.

DeepSeek claims it achieved advanced AI performance using just 2,048 H800 GPUs over 57 days at a cost of under $6 million—reportedly 95% cheaper than OpenAI’s models.

While some, including LikeFolio co-founder Andy Swan, see this as Chinese propaganda, the market’s reaction has been anything but dismissive.

But here’s the thing: we believe the market’s knee-jerk reaction is overblown. In fact, DeepSeek’s announcement may actually highlight opportunities for Nvidia and smaller players in the AI space.

Let’s break it down.

DeepSeek’s Claims: What’s Really Going On?

While DeepSeek’s narrative focuses on low-cost innovation, industry insiders suggest the story isn’t so straightforward. Evidence points to DeepSeek potentially using tens of thousands of Nvidia H100 GPUs—not just 2,048 H800s—to achieve its results.

Moreover, the $6 million cost cited by DeepSeek likely excludes significant operational expenses like energy, cooling, and storage—essential components for training large-scale AI models.

This doesn’t diminish DeepSeek’s breakthrough. Instead, it highlights how cost reductions—whether through optimized software, hardware efficiency, or both—are opening doors for smaller companies to enter the AI race.

For investors, this is a game-changer.

Low-cost innovation could democratize AI development, making it accessible to startups and small-cap firms. And that’s where the real opportunity lies.

Nvidia’s Role in a Democratized AI Market

DeepSeek’s success, whether through engineering optimizations or leveraging Nvidia’s GPUs, signals a broader shift in the AI landscape.

While tech giants like Microsoft, Meta, Amazon, and Alphabet continue to dominate GPU demand—collectively purchasing over 1.1 million H100 GPUs in 2024—smaller companies now have a clearer path to competing in the AI market.

This democratization of AI development could spark a new wave of innovation driven by startups and mid-sized firms. And Nvidia is uniquely positioned to benefit.

For smaller companies, Nvidia’s mid-tier GPUs like the H800, along with its cloud-based AI infrastructure, provide accessible options for building and deploying AI systems without requiring massive upfront investments.

For larger players, Nvidia’s high-end GPUs remain indispensable for staying ahead in the AI race.

Capital expenditures on AI infrastructure are already growing at a blistering pace, and Nvidia stands to gain from both ends of the market.

Bottom Line: Opportunities for Investors

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