Meta and NVIDIA: The Future of Data Centre Infrastructure

Meta is deepening its multiyear partnership with NVIDIA to support the next phase of its AI data centre expansion, committing to large-scale deployments of CPUs, networking and millions of GPUs across hyperscale facilities.

The agreement spans on-premises and cloud environments and underpins Meta’s long-term AI infrastructure roadmap.

The company plans to build data centres optimised for both training and inference, integrating NVIDIA Grace CPUs, Blackwell and Rubin GPUs and Spectrum-X Ethernet networking into its production architecture.

The collaboration highlights how tightly coupled compute, networking and software stacks are becoming as AI clusters scale to unprecedented levels.

Hyperscale clusters for training and inference

Under the partnership, Meta will deploy industry-leading NVIDIA GB300-based systems and create a unified architecture across its own data centres and NVIDIA Cloud Partner environments.

The objective is to simplify operations while maximising performance and scalability.

“No one deploys AI at Meta’s scale – integrating frontier research with industrial-scale infrastructure to power the world’s largest personalisation and recommendation systems for billions of users,” says Jensen Huang, Founder and CEO at NVIDIA.

“Through deep codesign across CPUs, GPUs, networking and software, we are bringing the full NVIDIA platform to Meta’s researchers and engineers as they build the foundation for the next AI frontier.”

Mark Zuckerberg, Founder and CEO of Meta, adds: “We’re excited to expand our partnership with NVIDIA to build leading-edge clusters using their Vera Rubin platform to deliver personal superintelligence to everyone in the world.”

Expanding Grace CPU deployment

A core element of the agreement is the expanded deployment of ARM-based NVIDIA Grace CPUs within Meta’s production data centre applications.

The companies describe this as the first large-scale Grace-only deployment, supported by joint optimisation of CPU ecosystem libraries.

The aim is to improve performance per watt with each generation, aligning with Meta’s strategy to increase compute density while controlling power consumption.

Meta and NVIDIA are also collaborating on the deployment of NVIDIA Vera CPUs, with potential for large scale roll out in 2027.

For hyperscale campuses already operating at gigawatt levels, incremental gains in performance per watt can translate into significant reductions in overall energy use.

By combining CPU optimisation with GPU acceleration, Meta is refining a heterogeneous architecture designed for large-scale AI workloads.

Networking and unified architecture

To support distributed AI clusters, Meta has adopted the NVIDIA Spectrum-X Ethernet networking platform across its infrastructure footprint.

The platform is intended to deliver predictable low-latency performance while maximising utilisation.

In high-performance AI environments, networking is critical to ensuring GPUs remain efficiently interconnected.

Spectrum-X will be integrated into Meta’s Facebook Open Switching System platform, supporting AI scale throughput across training and inference workloads.

The unified architecture will span on-premises data centres and partner cloud environments, providing a consistent operational model across deployments.

For operators, this approach can reduce integration complexity and support faster scaling of new clusters.

Confidential computing for WhatsApp

Beyond compute and networking, the partnership extends to data protection. Meta has adopted NVIDIA Confidential Computing for WhatsApp private processing, enabling AI powered features while preserving user data confidentiality and integrity.

NVIDIA and Meta are working to expand confidential compute capabilities beyond WhatsApp to additional use cases across Meta’s portfolio.

For data centre environments hosting sensitive AI workloads, confidential computing adds hardware-based security layers to protect data in use.

Engineering teams from both companies are engaged in ongoing co-design to optimise state of the art AI models across Meta’s core workloads.

By aligning silicon, networking and software, the companies aim to deliver higher performance and efficiency for AI capabilities deployed at global scale.

The partnership positions Meta’s next-generation data centres around a tightly integrated NVIDIA stack, combining Grace and Vera CPUs, Blackwell and Rubin GPUs, Spectrum-X networking and confidential computing within a unified hyperscale architecture.