Despite talk of an impending AI bubble, Amazon is the latest company to benefit from the AI arms race. Meta just inked a deal with Amazon worth billions to deploy the AWS Graviton processors in its 32 data centers over the next three years. While Amazon hasn’t disclosed the full value of the deal, we’ve seen companies spend eye-popping sums to sustain their AI growth.
Recently, Meta also signed a six-year, $10 billion deal with Google Cloud, while OpenAI agreed to spend $20 billion with chip startup Cerebras over the next three years to use servers powered by the company’s hardware.
The Graviton processors support cloud workloads that run on Amazon Elastic Compute Cloud (Amazon EC2), and the company has long said that it offers the best price performance for cloud workloads.
What’s interesting here is that the AWS Graviton is an ARM-based CPU, rather than a GPU. CPU refers to a computer’s Central Processing Unit, the computer’s brain, whereas a GPU is its Graphics Processing Unit, commonly used for training AI models.
“As we scale the infrastructure behind Meta’s AI ambitions, diversifying our compute sources is a strategic imperative,” said Santosh Janardhan, Meta’s head of infrastructure, in a statement. “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.”
Meta has been a long-time AWS customer, so this chip deal doesn’t come as a surprise. What’s notable is that it involves CPU chips rather than GPU.
Typically, AI models are trained on GPUs. Once trained, AI agents can use CPUs for more compute-intensive workloads, such as writing code.
The Graviton chips are designed to be efficient for AI-agentic tasks. According to Amazon, the Graviton 5 chips have 192 cores and a cache that is five times larger than the previous generation, reducing communication delays between cores by 33%. They should also be more energy-efficient, with 25% better performance than previous generations.
“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, AWS vice president, in a statement.
Part of the motive behind this may also be that earlier this month, Antropic signed a deal to spend $100 billion on AWS to run Claude workloads on Amazon’s Trianium GPU chips, while Amazon agreed to invest $5 billion back into Antropic. It’s likely that Antropic has monopolized Amazon’s stock of Tranium2 to Tranium4 chips, and the company also has the option to buy future Amazon chips as they become available.
In addition to working with Amazon, Meta is developing its own in-house silicon, with work progressing on four iterations of its MITA chip for AI and an expanded partnership with Broadcom to design and build the chips. Meta has also agreed to spend billions on chips and AI hardware from Nvidia and AMD, as well as another multibillion-dollar deal to use tensor processing units from Alphabet.
A Meta representative declined to share specific workloads but said the company will support AI work, including MSL (Meta SuperIntelligence Labs).
