Meta Expands AWS Partnership to Leverage Graviton CPUs to Power AI Agents
The move marks one of the largest CPU-based AI infrastructure expansions to date.
Meta Platforms has significantly expanded its partnership with Amazon Web Services (AWS), announcing plans to deploy tens of millions of Graviton processor cores to support its growing portfolio of artificial intelligence systems.
The move marks one of the largest CPU-based AI infrastructure expansions to date. While graphics processing units (GPUs) remain essential for training large models, Meta is increasingly turning to CPUs like AWS’s Graviton chips to handle inference and real-time workloads such as reasoning, orchestration, and code generation.
“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. 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,” Nafea Bshara, Amazon VP, Distinguished Engineer, said.
The deployment will initially involve tens of millions of Graviton cores, with the flexibility to expand further as demand grows. This scale positions Meta among the largest users of AWS’s custom silicon globally and highlights the rising importance of diversified compute strategies in the AI era.
“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, Meta Head, Infrastructure.
Industry analysts say the deal reflects a growing trend among major technology companies to adopt custom-designed chips to reduce costs and improve performance.
AWS’s Graviton processors, based on Arm architecture, are designed to deliver better price-performance and energy efficiency compared to traditional server chips.
The Graviton5 chip features 192 cores and a cache that is five times larger than the previous generation, which reduces delays in how quickly those cores communicate with each other by up to 33%. That means faster data processing with greater bandwidth—key requirements for agentic AI systems that need to continuously reason through and execute multi-step tasks.
"These are production systems that reason, plan, and operate in real time at global scale. That changes the infrastructure requirements. Graviton was built for this kind of workload: sustained, efficient compute with low-latency communication between cores," Matt Garman, AWS CEO, said.
