Meta expands Nvidia partnership with millions of new AI chips

Meta (META) just doubled down on Nvidia (NVDA).

The company will deploy millions of Nvidia AI chips across its U.S. data centers under a sweeping new agreement announced Tuesday.

This deal includes Nvidia’s next-generation GPUs, its Grace CPUs as standalone processors, future Vera CPUs in 2027, Spectrum-X networking gear, and security tech tied to WhatsApp.

The price wasn’t disclosed, but analysts peg it in the tens of billions.

Meta already said it plans to spend up to $135B on AI in 2026 and $600B in the U.S. by 2028 on data centers and infrastructure. This Nvidia deal will swallow a huge chunk of that.

Meta will become the first company to deploy Nvidia’s Grace CPUs as standalone chips at scale, not just bolted next to GPUs. That means Meta isn’t just buying accelerators. It’s rebuilding the entire AI stack around Nvidia silicon.

CEO Mark Zuckerberg framed it as a push toward “personal superintelligence.” We also know that Meta`s AI glasses sales have tripled in 2025, so Meta is heavily investing in what pays, AI.

The disruption behind the news: This locks in Nvidia as the operating system of AI infrastructure. Again.

When one company deploys millions of chips from a single vendor, that vendor’s software stack becomes the default.

We are also wondering how soon can China's AI chips catch Nvidia?

CUDA, networking, optimization tools, developer workflows.

Switching costs explode.

Once Meta trains its next-generation Avocado models on Nvidia hardware, porting them to AMD or Google TPUs becomes expensive, slow, and risky.

That’s the first disruption. Vendor gravity. The more Meta scales Nvidia, the harder it is to leave. Nvidia stops being a supplier and becomes embedded infrastructure.

Second, cost curves get weaponized. At “millions” of units, Meta likely negotiated pricing far below list. If a top-end AI GPU carries a street price north of $30,000, even a modest discount across 1M units swings $5B to $10B. That scale lets Meta train bigger models cheaper than most competitors can even buy hardware. Smaller AI labs won’t just be behind on talent. They’ll be behind on physics and economics.

Third, this shifts power inside Meta. Deploying standalone Grace CPUs signals that Meta is rethinking server architecture itself. If the CPU layer is optimized for AI workloads, not generic cloud tasks, every internal team will build for AI-first infrastructure. That means AI features move from experiments to defaults across Facebook, Instagram, and WhatsApp.

For consumers, this means AI baked into every product surface whether they asked for it or not. For advertisers, it means more automated campaign generation and targeting. For developers, it means tighter integration with Meta’s models and fewer open escape routes.

And for Nvidia’s stock, this cements demand visibility years out. When a single customer is committing at this scale, it stabilizes revenue in a market that was supposed to cool off.

What to watch next

Watch Meta’s capital intensity.

If AI capex hits $135B in 2026 as projected, depreciation alone could run tens of billions annually.

That pressure will force aggressive monetization of AI features.

Expect subscription layers, enterprise APIs, and ad pricing experiments.

Watch competitors’ supply constraints.

If Meta is absorbing millions of top-tier chips, availability tightens for everyone else. That could slow startups and push more companies into Nvidia’s cloud partnerships instead of building their own infrastructure.

Watch internal silicon efforts.

Meta develops its own chips and works with AMD. If those programs stall, Nvidia’s leverage grows. If they succeed, the next disruption is vertical integration.

But here’s the bottom line. Meta just decided that owning AI infrastructure at massive scale is more important than near-term profit optics. When a company commits hundreds of billions to one technological direction, it doesn’t plan to be second place. So we can also ask another question, is there a future coming where AI glasses replace our phones?

Meta (META) and Nvidia (NVDA) have a Disruption Score of 4. Click here to learn how we calculate the Disruption Score. 

Meta and Nvidia are also part of the Disruption Aristocrats, our quarterly list of the world’s top disruptive stocks.