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Over the past 25 years, I’ve made it my mission to speak up when something feels off in the markets.

A month before the dot-com bubble burst, I published a warning essentially saying: “This can’t last.”

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But what I see happening right now… it’s much bigger.

Some are even calling it, “The bubble to burst them all.”

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Exclusive News from MarketBeat.com

Meta Platforms May Ditch NVIDIA Chips—Here’s Why Investors Care

Reported by Leo Miller. Published: 11/29/2025. 

What You Need to Know

• Shares of Meta Platforms rose considerably on Nov. 25, aiding the stock’s recent recovery.
• Meta is a big-time buyer of NVIDIA chips. It may be looking to shift spending to two other AI giants.
• Tensor processing units could offer a counterweight to Big Green, leading to lower costs for Meta over time.

After weeks of losses, shares of Meta Platforms (NASDAQ: META) are staging a moderate recovery.

The stock hit a six-month low of around $589 on Nov. 20.

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As of the Nov. 25 close, shares were trading at $636, about 8% above that trough.

The broader market rebound has helped: the S&P 500 was up roughly 3.5% over the same period.

Meta’s outperformance, however, suggests company-specific factors are also supporting the stock.

A Nov. 25 report said Meta is exploring the possibility of using artificial intelligence (AI) chips developed by two of the world’s biggest names in technology.

Meta May Be Pushing Back on NVIDIA

As first reported by The Information, Meta is considering using tensor processing units (TPUs) to support its AI ambitions. TPUs are custom AI chips from Google’s parent company, Alphabet (NASDAQ: GOOGL), co-developed with semiconductor giant Broadcom (NASDAQ: AVGO). Most AI-chip spending, including Meta’s, has gone to NVIDIA’s (NASDAQ: NVDA) graphics processing units (GPUs). Exploring TPUs could have several positive implications that the market may be acknowledging.

First, TPUs could check NVIDIA’s pricing power. NVIDIA currently commands premium pricing because its GPUs lead on performance. If another chip architecture can match that performance, NVIDIA’s ability to charge high prices could be reduced, lowering costs for chip buyers. That would be especially beneficial for Meta, since concerns about escalating AI spending have weighed on the stock.

Google recently released its Gemini 3 Pro large language model (LLM), which experts believe was trained primarily on TPUs. Some respected LLM evaluation sites now rank Gemini 3 Pro as the world’s top-performing model, suggesting TPUs may be a viable alternative to NVIDIA GPUs. If so, Meta could potentially train its own LLMs at lower long-term cost. That said, this doesn’t mean Meta will stop being a large NVIDIA customer—TPUs would more likely serve as an additional resource.

Markets may also welcome Meta’s exploration of new approaches to developing its LLaMa models. LLaMa has generally lagged behind the top models: the Artificial Analysis Intelligence Index gives LLaMa 4 Maverick a score of 36 versus Gemini 3 Pro’s 73, less than half. Meta’s interest in TPUs could signal a reevaluation of its training approach to improve performance, but meaningful gains would take time and require substantial investment.

Meta Has a History of Custom-Chip Success

Although LLaMa hasn’t impressed, Meta has made significant progress with other AI systems that power its core business—ranking and recommendation algorithms that determine what content and ads appear on Facebook and Instagram.

Meta’s advertising results indicate those systems are working well.

Advertising revenue growth has accelerated every quarter in 2025, and Meta’s 26% revenue growth in Q3 is its highest since Q1 2024.

The company uses the Meta Training & Inference Accelerator (MTIA) to support those ranking and recommendation systems.

MTIA is Meta’s custom chip, widely believed to have been co-developed with Broadcom. That track record shows Meta has successfully used non‑NVIDIA silicon before.

TPUs could therefore help Meta optimize and diversify its AI infrastructure.

Moreover, Meta’s MTIA experience suggests integrating TPUs would not require venturing into completely uncharted territory.

Investor Sentiment Rises on Potential TPU Integration

For now, investors must wait to see whether TPUs become a meaningful part of Meta’s AI stack. Still, the company’s willingness to explore TPUs appears to be restoring some confidence amid concerns about AI spending. It will be notable if Meta addresses TPUs on its next earnings call or beforehand.

Notably, on Nov. 24 analysts at BNP Paribas set an $800 price target on Meta shares, implying nearly 26% upside versus the stock’s Nov. 25 close.

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