NVDA: Nvidia Drops 2.4% on Report Google Plans to Sell AI Chips to Meta. Now What?

Is the king of AI challenged? Likely yes. With demand at fever pitch, any dent at the profit margin could hurt big time.

⚠️ Chip Shock for Nvidia Stock

• Nvidia NVDA dropped 2.4% after falling as much as 7% intraday when reports surfaced that Meta META is considering buying Google’s custom TPUs – tensor processing units built specifically for AI workloads.
• Alphabet GOOGL gained another 1.5% after Monday’s monster rally, as investors cheered the idea of Google supplying AI hardware.
• While Nvidia’s crown isn’t falling off just yet, the message is clear: even the king can get poked.

🤖 TPU vs. GPU

• Nvidia’s GPUs dominate AI training and inference today, but Google’s TPUs are custom-built accelerators that promise more efficiency for specific AI tasks. For clients spending billions, “more efficient” translates directly to “cheaper to run.”
• Meta’s interest in using Google’s chips in 2027, and potentially renting them from Google Cloud as early as next year, signals a push toward diversification. Big AI builders want more than one supplier, especially after years of Nvidia scarcity.
• Experts say Google’s vertical integration (building chips, running data centers, selling cloud) gives it an edge in offering turnkey AI infrastructure. Nvidia still leads, but the moat suddenly looks a bit shallower.

🏆 AI Infrastructure Spending Sky-High

• Meta is set to spend up to $72 billion on AI infrastructure this year. When a buyer that large starts shopping around for alternatives, it can reshape supply dynamics across the entire semiconductor industry.
• Nvidia’s margins have been stratospheric thanks to unprecedented demand. But even a small dent via competition, price pressure, or shifting customer loyalties can hit earnings hard at this scale. That’s why the stock reacted instantly.
• The broader takeaway: the AI hardware race is maturing. Nvidia is still king, but it no longer rules uncontested. As 2027 approaches, expect more headlines, more chip rivalries, and more volatility in the AI semiconductor throne room.