Meta teams up with Nvidia to build massive AI infrastructure for future projects

Meta has signed a multi-year partnership with Nvidia to develop large-scale artificial intelligence infrastructure, marking a significant step in the company’s push to expand its AI capabilities across products and services. The collaboration focuses on building hyperscale computing systems designed to support some of the biggest AI workloads in the technology industry.

The partnership will involve deploying millions of graphics processing units and Arm-based central processing units, expanding networking capacity, and introducing privacy-focused computing technologies across Meta’s platforms. Both companies say the effort is intended to combine Meta’s large production workloads with Nvidia’s hardware and software stack to improve performance, efficiency and scalability.

Building a unified AI infrastructure

The companies are working to create a unified infrastructure architecture that connects Meta’s on-premises data centres with Nvidia’s cloud partner deployments. This unified approach is intended to simplify operations while providing scalable resources for training and running AI models.

NVIDIA chief executive Jensen Huang highlighted the scale of Meta’s ambitions, saying, “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.” He added that Nvidia is bringing its full platform to Meta’s engineers through close collaboration across CPUs, GPUs, networking and software.

The new infrastructure will rely on Nvidia’s GB300-based systems, which integrate computing, memory and storage to handle next-generation AI workloads. Meta is also expanding Nvidia Spectrum-X Ethernet networking across its infrastructure to deliver predictable, low-latency performance. The companies say this will also improve operational and energy efficiency for large-scale AI tasks.

By unifying infrastructure across different environments, Meta aims to accelerate the deployment of AI applications while reducing complexity. The approach reflects a broader industry trend, in which companies are investing heavily in integrated platforms to support increasingly large and complex AI models.

Focus on privacy, performance and efficiency

A key part of the partnership is the adoption of Nvidia Confidential Computing, which Meta has already begun using to support AI-powered features in WhatsApp. This technology allows machine learning models to process user data while maintaining privacy and data integrity, an issue that has drawn increasing scrutiny from regulators and users.

Meta plans to extend privacy-enhancing AI techniques to other services and integrate them across its platforms. The company believes this will enable new AI-driven features without compromising user trust, an area that has historically been a challenge for the firm.

Engineering teams from both companies are collaborating to code-sign AI models and optimise software across the entire infrastructure stack. By aligning hardware, software, and workloads, Meta and Nvidia aim to improve performance per watt and accelerate training for advanced AI models.

Large-scale deployment of Nvidia Grace CPUs is also central to the initiative, representing one of the first major deployments of Grace-only systems at this scale. NVIDIA is also optimising CPU ecosystem libraries to improve throughput and energy efficiency, helping Meta manage the growing computational demands of future AI workloads.

Strategic implications for Meta and Nvidia

The partnership underscores Meta’s ambition to remain competitive in the AI race, where companies such as OpenAI, Google and Microsoft are investing billions in infrastructure and model development. By securing long-term access to Nvidia’s latest hardware platforms, Meta is positioning itself to build and deploy increasingly powerful AI systems across social media, messaging, and emerging platforms.

Mark Zuckerberg, Meta’s chief executive, emphasised the company’s broader vision, stating, “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.” The reference to Nvidia’s upcoming platform signals Meta’s intent to stay at the forefront of AI computing for years to come.

For Nvidia, the deal further strengthens its role as a critical supplier of AI hardware and software. The company’s GPUs and networking products have become essential for training large AI models, and partnerships with major technology firms reinforce its position in the AI ecosystem.

Industry analysts say the collaboration reflects a growing trend towards deeper integration between AI developers and hardware providers. As models become larger and more complex, companies are increasingly seeking custom infrastructure solutions to maximise performance and reduce costs.

The partnership also highlights the increasing importance of energy efficiency in AI development. With data centres consuming vast amounts of power, improving performance per watt has become a key metric for companies deploying AI at scale.

Overall, the Meta-NVIDIA partnership signals a major investment in the infrastructure needed to support the next generation of AI applications. By combining large-scale computing resources with privacy-preserving technologies and software optimisation, both companies aim to push the boundaries of what AI systems can achieve in consumer and enterprise applications.