Meta and AMD Form a Multiyear, $100 Billion AI Chip Partnership

There's a number that keeps coming up in tech right now, and it's so big it almost stops making sense — $100 billion. That's what Meta has committed to spending on AMD chips in a sweeping multiyear deal the two companies announced on February 24, 2026. We're not talking about a handshake agreement, either. This is a structured, performance-tied deal that includes AMD issuing Meta a warrant for up to 160 million shares of AMD common stock — roughly 10% of the company — at just $0.01 per share.

The catch? The full stock award is conditional. AMD's share price would need to hit $600 for Meta to receive its final tranche. On the day of the announcement, AMD closed at $196.60. So there's a long runway ahead — and that's kind of the whole point. Both companies are betting on each other's future, not just today's business.

The deal gives Meta access to AMD's MI540 series GPUs and its latest generation of CPUs, and together, those chips are expected to drive roughly six gigawatts of data center power demand. To put that in perspective, a single gigawatt can power roughly 750,000 homes. Six of them, for AI chips alone.

Why CPUs Are Suddenly at the Heart of AI Infrastructure

The Shift From GPU Dominance to CPU-Inclusive AI Stacks

Here's something that might surprise you — CPUs are making a comeback in AI. For a while, it felt like the conversation was all GPUs, all the time. But the landscape is shifting. CPUs are increasingly becoming a core pillar of the AI inference compute stack, and there are good reasons for that.

They're more efficient for inference workloads. They're easier to scale. And — maybe most importantly — they don't lock companies into a single vendor. That last part matters a lot right now.

AMD CEO Lisa Su put it plainly during a Tuesday investor briefing: "The CPU market is absolutely on fire. There is significant demand. It has continued to grow, and it really is a result of the AI infrastructure deployments as inferencing scales, as agentic AI scales, and our portfolio is in an extremely good position."

That's not just optimism. That's a signal that the entire compute stack for AI — not just training, but the ongoing work of running models in production — is being reconsidered from the ground up.

AMD's Growing Role as a Credible Nvidia Alternative

How AMD Is Capitalizing on the Semiconductor Supply Power Shift

Nvidia has been the dominant force in AI chips for years. And honestly, they've earned it. But they've also charged a premium for that dominance — and as AI spending scales into the hundreds of billions, companies are actively looking for alternatives.

AMD is stepping into that gap. Last October, AMD struck a similar deal with OpenAI — trading equity for a commitment to purchase chips worth tens of billions. Now Meta is following the same playbook. The structure isn't accidental. By issuing performance-based warrants, AMD aligns its financial future with its biggest customers' success. If Meta's AI ambitions pay off, AMD's stock climbs. If AMD's stock climbs, Meta's warrant becomes worth something staggering. It's a bet made together.

This kind of equity-linked deal is becoming a new model for the semiconductor industry — and it signals that the relationship between chip makers and AI hyperscalers is deepening into something more like a long-term partnership than a vendor-client transaction.

Mark Zuckerberg's Vision for Personal Superintelligence

Defining "Personal Superintelligence" and What It Means for Meta's AI Strategy

Mark Zuckerberg called the AMD partnership "an important step" as Meta works toward what he's calling personal superintelligence — and that phrase deserves some unpacking.

Personal superintelligence, as Zuckerberg defines it, isn't about a single godlike AI system running everything. It's about AI systems that deeply understand and empower individuals in their everyday lives. Think less science fiction overlord, more like a deeply knowledgeable companion that knows your context, your goals, your preferences — and acts accordingly.

That's a meaningful distinction. It repositions AI from a tool you use occasionally to something closer to an always-on collaborator. And to build that, you need compute at a scale that matches the ambition. Hence the $100 billion chip deal. Hence the $600 billion in U.S. data center and AI infrastructure spending Meta has pledged over the next several years. Hence the $135 billion in projected capital expenditure for 2026 alone.

The math only makes sense if you believe the end product is genuinely transformative. Zuckerberg clearly does.

Meta's Massive Data Center Expansion Across the U.S.

The $600 Billion AI Infrastructure Commitment and the Indiana Campus

The AMD deal doesn't exist in isolation — it's one piece of what is shaping up to be one of the largest infrastructure buildouts in American history. Meta has pledged at least $600 billion toward U.S. data centers and AI infrastructure over the coming years, with $135 billion earmarked just for 2026.

One of the most notable projects in that pipeline is a $10 billion gas-powered data center campus in Indiana, designed to handle one gigawatt of compute capacity on its own. The gas-power choice has drawn some criticism, but the scale of the facility signals how serious Meta is about owning its own compute destiny rather than relying purely on cloud providers.

This is what it looks like when a tech company decides that AI isn't a feature — it's the entire product roadmap.

Meta's Multi-Vendor Chip Strategy: AMD, Nvidia, and In-House Silicon

Balancing Nvidia Partnerships With AMD and Proprietary Chip Development

Just weeks before the AMD deal, Meta signed a multiyear agreement with Nvidia to expand its data centers with millions of Nvidia's latest CPUs and GPUs. So Meta isn't abandoning Nvidia — it's making sure it's never too dependent on them, either.

And it goes further. Meta has been developing its own in-house chips, though that effort has reportedly hit delays. The direction is clear even if the timeline is fuzzy: Meta wants to control its compute stack from multiple angles — third-party commodity chips from AMD, premium GPUs from Nvidia, and eventually proprietary silicon tuned specifically for Meta's workloads.

It's a hedge, but it's also a strategy. Diversifying chip sources means more negotiating leverage, more resilience against supply chain disruptions, and eventually, the ability to optimize hardware for exactly what Meta's AI systems need rather than adapting to what's available.