Meta has signed a deal to deploy tens of millions of AWS Graviton processor cores as it expands the computing backbone needed for its next generation of artificial intelligence systems.

The agreement deepens Meta’s long-running relationship with Amazon Web Services and highlights a growing shift in AI infrastructure. While graphics processors remain central to training large AI models, companies are now seeking more CPU power for inference, real-time reasoning, search, coding tools, and multi-step AI agents.

Amazon said the rollout will begin with tens of millions of Graviton cores and can expand further as Meta’s AI demand grows. The chips are expected to power a range of Meta workloads tied to AI services used by billions of people across its platforms.

The move also reflects rising demand for custom silicon that can reduce cost and energy use while delivering performance at hyperscale.

CPU race begins

AWS Graviton chips are Amazon’s in-house processors built on Arm architecture. They are designed to run cloud workloads faster, cheaper, and with lower power consumption than many traditional server chips.

The latest Graviton5 chip uses a 3-nanometer manufacturing process and includes 192 cores. Amazon said it offers up to 25 percent better performance than the previous generation.

The company also said Graviton5 carries a cache five times larger than the prior version, helping cut delays in communication between cores by up to 33 percent. That matters for AI systems that need to rapidly process data while coordinating many tasks at once.

Graviton processors run on the AWS Nitro System, Amazon’s hardware and software stack designed to improve security, networking, and performance. The chips also support Elastic Fabric Adapter technology, which enables low-latency communication across large clusters of servers.

AI demand shifts

As AI products evolve, the industry is moving beyond model training alone. Newer agentic AI systems are expected to handle planning, coding, reasoning, and task execution in real time, creating heavy demand for CPUs alongside GPUs.

“This isn’t just about chips; it’s about giving customers the infrastructure foundation, as well as data and inference services, to build AI that understands, anticipates, and scales efficiently to billions of people worldwide,” said Nafea Bshara, vice president and distinguished engineer, Amazon.

“Meta’s expanded partnership, deploying tens of millions of Graviton cores, shows what happens when you combine purpose-built silicon with the full AWS AI stack to power the next generation of agentic AI.”

Meta said expanding compute sources is now a strategic priority as it scales AI operations.

“As we scale the infrastructure behind Meta’s AI ambitions, diversifying our compute sources is a strategic imperative. AWS has been a trusted cloud partner for years, and expanding to Graviton allows us to run the CPU-intensive workloads behind agentic AI with the performance and efficiency we need at our scale,” said Santosh Janardhan, head of infrastructure, Meta.

The deal also underscores how energy efficiency is becoming a bigger factor in AI buildouts. As compute demand surges, chip efficiency can directly affect operating costs, power availability, and sustainability goals.

For Amazon, the agreement gives Graviton one of its biggest public endorsements yet. For Meta, it offers another route to scale AI infrastructure beyond traditional processor suppliers.