Nvidia and Meta Expand Partnership with Millions of AI Chips

Feb 18, 2026, 2:18 AM

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Nvidia (NVDA) and Meta (META) have unveiled a significant expansion of their partnership, which will see Nvidia supply millions of its Blackwell and Rubin GPUs, alongside CPUs and networking solutions, to Meta. This collaboration aims to enhance Meta's data centers, supporting the training and execution of advanced AI models.

Nvidia's CEO Jensen Huang emphasized the scale at which Meta deploys AI, stating, "No one deploys AI at Meta's scale - integrating frontier research with industrial-scale infrastructure to power the world's largest personalization and recommendation systems for billions of users". The integration of Nvidia's technologies is expected to provide Meta's researchers and engineers with the tools necessary to build the next generation of AI applications.

As part of the deal, Meta will also be implementing its first large-scale deployment of Nvidia's Grace CPU-only servers, with plans to introduce Vera CPU-only systems by 2027. These new systems are designed to operate similarly to the traditional servers that Meta currently uses, which predominantly rely on Intel chips. This shift could challenge Intel and AMD's long-standing dominance in the CPU server market.

In addition to GPUs, Nvidia's Confidential Computing technology will be employed by Meta to enhance privacy in data processing, particularly within its WhatsApp messaging app. This move not only strengthens the security of user data but also allows for the integration of AI capabilities across Meta's various platforms.

The expanded partnership comes at a time when AI-related stocks have faced challenges, with concerns about spending and the necessity of high-powered GPUs for all AI applications. Meta's stock has seen a decline of 3.3%, while other tech giants, including Microsoft, have also experienced significant losses this year. Nvidia's stock is down by more than 1% year to date, and AMD has fallen over 5% in the same period.

Despite these market fluctuations, analysts suggest that Nvidia is unlikely to lose its competitive edge in the AI sector. The versatility of GPUs for a wide array of AI applications contrasts with specialized chips like Google's TPUs and Amazon's Trainium processors, which are more limited in their use cases.

Meta's strategy to build hyperscale data centers optimized for AI workloads is indicative of its long-term vision for AI infrastructure. This partnership with Nvidia is poised to deliver significant improvements in performance and efficiency across Meta's platforms, effectively positioning the company for future advancements in AI technology.

As the collaboration progresses, both companies are expected to engage in further deep codesign efforts, enhancing AI models tailored for Meta's extensive user base. This strategic partnership not only marks a pivotal moment for both Nvidia and Meta but also highlights the ongoing evolution of AI technology in the digital landscape.

In conclusion, the expanded partnership between Nvidia and Meta represents a significant milestone in the integration of AI technologies into everyday applications, setting the stage for future innovations that could reshape user interaction across various digital platforms. The focus on performance, efficiency, and privacy reflects a commitment to advancing AI while addressing the challenges faced by the industry today.

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