Meta is doubling down on its AI strategy through an expanded agreement with Nvidia that will see millions of chips deployed across its artificial intelligence data centers. The deal includes Nvidia’s new standalone Grace CPUs and next-generation Vera Rubin systems.

Financial terms were not disclosed, but analysts estimate the agreement is worth tens of billions of dollars. This aligns with Meta’s previously announced plan to invest up to $135 billion in AI infrastructure in 2026, as part of a broader $600 billion U.S. infrastructure commitment through 2028.

What’s New in This Deal

While Meta has relied on Nvidia GPUs for over a decade, this agreement represents a deeper and broader technology partnership.

1. Standalone Grace CPUs at Scale

For the first time, Meta will deploy Nvidia Grace CPUs as standalone processors in its data centers, rather than pairing them exclusively with GPUs inside hybrid servers.

This marks the first large-scale standalone Grace CPU deployment and reinforces Nvidia’s end-to-end infrastructure strategy, spanning CPU, GPU, networking, and system-level optimization.

Grace is optimized for inference and agentic workloads, complementing systems like Grace Blackwell and Vera Rubin. The move signals Meta’s intention to architect AI infrastructure with tightly integrated compute layers.

2. Next-Generation GPU Roadmap Secured

Meta will deploy:

Blackwell GPUs, currently in high demand and previously back-ordered
Rubin GPUs, recently entering production
Vera CPUs, planned for deployment in 2027

Securing supply across multiple chip generations gives Meta a strategic advantage in a market constrained by global AI hardware demand.

3. Advanced Networking and Security Integration

The agreement also includes Nvidia’s Spectrum-X Ethernet networking technology, designed to interconnect GPUs at hyperscale within AI clusters.

In addition, Meta will integrate Nvidia’s security capabilities into AI features across WhatsApp, extending the partnership beyond core data center infrastructure into consumer-facing AI applications.

Infrastructure at Hyperscale

Meta plans to build 30 data centers, 26 of which will be located in the United States. Two of the largest AI facilities are already under construction:

Prometheus, a 1-gigawatt site in New Albany, Ohio
Hyperion, a 5-gigawatt site in Richland Parish, Louisiana

These investments position Meta alongside hyperscale competitors such as Google and OpenAI in the race to control next-generation AI infrastructure.

Meta is not exclusively dependent on Nvidia. The company is exploring alternatives, including potential use of Google’s Tensor Processing Units and internally developed silicon. It also works with Advanced Micro Devices as part of a broader multi-vendor strategy.

Industry Implications

This partnership highlights three major trends shaping enterprise AI:

1. Full-Stack AI Infrastructure Is the New Battleground

Big Tech companies are no longer purchasing GPUs in isolation. They are investing in complete ecosystems that include CPUs, GPUs, networking, security, and co-optimized software.

2. Deep Hardware-Software Co-Design

Engineering teams from Meta and Nvidia will collaborate closely to optimize state-of-the-art AI models. This level of codesign improves latency, energy efficiency, and total cost per token at scale.

3. Supply Chain Control as a Competitive Edge

With Blackwell GPUs previously back-ordered and Rubin now entering production, securing early and large-scale supply is a strategic move in a constrained hardware environment.

What This Means for Meta’s AI Roadmap

Meta is developing a new frontier model, Avocado, as a successor to its Llama AI family. While recent releases have received mixed reactions from developers, the scale of infrastructure investment suggests a long-term strategy centered on performance, vertical integration, and product-level AI deployment.

For CTOs, CIOs, and infrastructure leaders, this announcement reinforces a critical shift:

The competitive advantage in AI will not come solely from model quality, but from how efficiently those models run at global scale.

Meta is betting on infrastructure. Nvidia is becoming the backbone of that strategy.

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