Meta signs multibillion-dollar deal for millions of AWS Graviton chips to power AI workloads

In another wild turn for AI chips, Meta signs deal for millions of Amazon AI CPUs | TechCrunch

Amazon just scored a major coup with Meta thanks, once again, to Amazon's own homegrown chips. Meta has signed a deal to use millions of AWS Graviton chips to power its growing AI needs, Amazon announced Friday. Note that the AWS Graviton is an ARM-based CPU, (a central processing unit, the chip that handles general computing tasks) not a GPU (a graphical processing unit). While GPUs remain the chip of choice for training large models, once those models are trained, AI agents built on top of them are causing a shift in the type of chip is needed. Agents create compute-intensive workloads like real-time reasoning, writing code, search, and the the coordination involved in managing agents through multi-step tasks. AWS's latest version of Graviton was designed specifically to handle AI-related compute needs, the company says. This deal brings more of Meta's cash back to AWS instead of competitors like Google Cloud. Last August, Meta signed a six year, $10 billion deal with Google Cloud, though Meta had, until then, primarily been an AWS customer that also used Microsoft Azure. We couldn't help but notice that AWS timed the announcement of this deal right as the Google Cloud Next conference wrapped up, like a virtual smirk at its cloud rival. Google, of course, also makes its own custom AI chips and announced new versions of them at the show. True, Amazon makes its own AI GPU as well: the Trainium, which, despite its name, is used for both training and inference -- the stage that happens after a model is trained, when it's actively processing prompts. But Anthropic had already swooped in with a deal announced earlier this month that commandeered many of those chips for years to come. The Claude maker agreed to spend $100 billion over 10 years to run its workloads on AWS -- with a particular focus on Trainium -- while Amazon agreed to invest another $5 billion (bringing its total to $13 billion of investment) into Anthropic in return. Ultimately, the Meta deal is allowing Amazon to showcase a huge AI customer as a proving point for its homegrown CPUs. These are chips that compete with Nvidia's new Vera CPU, which is also ARM-based and designed to handle AI agentic workloads. The difference, of course, is that Nvidia sells its chips and AI systems to enterprises and cloud providers (including AWS). AWS only sells access to its chips through its cloud service. Earlier this month Amazon CEO Andy Jassy took aim at Nvidia and Intel in his annual shareholder letter, saying that enterprises want better price-performance ratios for AI, and that he intends to win deals on that basis. This also means the pressure couldn't be higher on Amazon's internal chip building team to deliver, a team that we visited last month in an exclusive tour of their lab.

Meta Just Signed a Huge Deal to Use Amazon's Graviton CPU Chips for AI

Expertise 13+ years of experience in consumer product reviews, buying guides, best lists, and tech news across a variety of tech categories. As a homeowner, Ajay is also familiar with the unique electrical issues that can crop up in a prewar apartment building. 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." 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).

Meta to use millions of AWS Graviton cores

Meta plans to deploy tens of millions of Amazon Web Services' Graviton 5 CPU cores as part of a multi-year collaboration that will make the social network among the largest-ever consumers of the cloud giant's homegrown silicon. This compute will support Meta's agentic AI deployments. While GPUs remain essential for training and running generative AI models, the software frameworks necessary to harness those models still run on CPUs. Amazon's latest Graviton processors feature 192 of Arm's Neoverse V3 cores along with a substantially larger L3 cache and support for memory up to DDR5 8,800 MT/s. That combo deliver a 25 percent performance uplift compared to Graviton 4. In a statement Santosh Janardhan, Meta's head of infrastructure, characterized the collaboration with AWS as an effort to diversify the social networking company's compute fleet. "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," he said. Evidence of a diversification strategy is not hard to find, because over the past few months Meta has cozied up to ARM-based CPU designers. In February, the company revealed it was among the first to deploy Nvidia's standalone Grace CPUs at scale. Since then the social networking magnate also announced plans to deploy Nvidia's all new 88-core Vera CPUs. Then, in March, Arm revealed it worked closely with Meta to design its first branded datacenter silicon - the "AGI CPU" which packs 136 Neoverse V3 cores into a 300 watt part. Arm's new silicon won't make its way into Meta datacenters unit later this year. However, the similarities between the AGI CPU and Amazon's Graviton 5 chips means Meta can probably deploy in AWS for now and then bring those workloads in house again when Arm's silicon is finally ready. Adoption of Arm datacenter processors, particularly for AI applications, is expected to drive considerable gains for the British chip designer's market share. Analysts at Counterpoint Research recently predicted that by 2029, Arm-based CPUs will account for 90 percent of the AI ASIC server CPU market. "While x86 architectures currently maintain a significant presence in AI server infrastructure, our generation-by-generation analysis suggests this established stronghold is swiftly transitioning toward proprietary Arm-based designs," Counterpoint analyst David Wu said in a blog post. This shift arguably began with the launch of Nvidia's Grace CPUs in 2023. The Arm-based CPUs have since replaced x86-based parts from Intel and AMD in many of Nvidia's GPU systems. In December, AWS revealed it was swapping out Intel's CPUs in favor of its own in its Trainium 3 AI rack systems, and just this week, Google said it would do the same replacing the x86 chips found in its TPU clusters with its own Arm-based Axion chips. ®

Meta Inks Multibillion-Dollar Deal to Use Amazon Chips for AI

Amazon.com Inc. and Meta Platforms Inc. have struck a multibillion-dollar deal for the social-media giant to rent hundreds of thousands of Amazon's general-purpose chips for its AI efforts. The multiyear deal gives Meta access to the Graviton line of processors, Nafea Bshara, an Amazon vice president and co-founder of the company's Annapurna Labs chips unit, said in an interview. Artificial intelligence models capable of generating text or reasoning are typically built using graphics processing units from Nvidia Corp. But AI developers can use general-purpose central processing units like Graviton for related tasks, including generating the responses to queries after a model is trained, a process known as inference. "The GPUs are useless if you don't have the CPUs next to them," Bshara said. Most CPUs Amazon has deployed in its data centers in recent years have been Graviton processors, an achievement for a company once heavily reliant on Intel Corp. hardware. Amazon Chief Executive Officer Andy Jassy said recently that the company's silicon unit was on pace to generate $20 billion in sales over the course of a year, and that executives were mulling selling the chips -- to date found only in Amazon data centers -- to other companies for use in their server farms. The Meta-Amazon deal announced on Friday is the latest Big Tech tie-up as the industry scrambles to secure sufficient processors to power new and future AI models. OpenAI and Anthropic have said they're increasing their use of Amazon's in-house Trainium chips, AI accelerators the company markets as a cost-effective alternative to Nvidia's GPUs. Meta has taken a broad approach to securing chips for its AI efforts, citing a desire to diversify its partnerships to stay flexible. The company has signed megadeals with chipmakers like Nvidia and Advanced Micro Devices Inc. Meta is also spending aggressively to develop its own silicon to help reduce costs and decrease its dependence on third-party chipmakers. The company is currently developing four iterations of its MTIA chip for AI purposes, and recently announced an expanded partnership with Broadcom Inc. for help designing and building those chips. Meta has also agreed to spend billions on chips and other AI hardware from Nvidia and AMD. It recently signed a multibillion-dollar deal to use so-called tensor processing units from Alphabet Inc.'s Google.

Meta will adopt hundreds of thousands of AWS Graviton chips in latest AI infrastructure grab

Amazon's cloud unit said Friday that Meta has agreed to use Amazon's general-purpose Graviton chips in a deal that will run for at least three years. The arrangement demonstrates Meta's willingness under CEO Mark Zuckerberg to splurge so it can meet high computing demand, alongside technology peers such as Alphabet and Microsoft. In recent weeks Meta has signed deals worth a combined $48 billion with CoreWeave and Nebius, both of which rent out access to Nvidia graphics processing units, or GPUs, that run AI models. Amazon didn't disclose the value of its Meta deal. Meta is counterbalancing infrastructure expansions with head count reductions. On Thursday the company announced plans to lay off around 8,000 employees, or 10% of its workforce. Unlike Nvidia GPUs, Arm-based Graviton processors from top cloud Amazon Web Services can take care of a wide assortment of computing tasks, similar to Intel's or AMD's central processing units, or CPUs. But Graviton can still come in handy for AI workloads, specifically for refinements, or post-training, after models have been trained with large amounts of data using large-scale computing clusters. "Graviton is one of the most used platforms for pre training by a lot of foundation model companies, and Meta is now one the newest one," said Nafea Bshara, an AWS vice president and distinguished engineer. Bshara co-founded chip company Annapurna Labs, which Amazon acquired in 2015. Since then, Amazon has developed special-purpose chips for training and running AI models, among other components. Graviton has become a breakout hit, gaining adoption from Adobe, Apple and Snowflake. Earlier this week, Amazon-backed AI model builder Anthropic announced plans to use Graviton processors as well. AWS says Graviton delivers the best performance for a given price of all computing options available through the EC2 computing service, while using 60% less energy. Meta has used Graviton chips on a small scale, and now it will tap hundreds of thousands of the chips, making it one of the top five Graviton customers, Bshara said. The company has rented out Nvidia GPUs from AWS since 2017, he said. On Thursday Intel CEO Lip-Bu Tan told analysts that demand exceeds supply for its Xeon server chips. "For the last few years, the story around high performance computing was almost exclusively about GPU and other accelerators," Tan said. "In recent months, we have seen clear signs that the CPU is reinserting itself as the indispensable foundation of the AI era." But Meta did not choose Graviton because other kinds of CPUs were unavailable, Bshara said. "Expanding to Graviton allows us to run the CPU-intensive workloads behind agentic AI with the performance and efficiency we need at our scale," Santosh Janardhan, Meta's head of infrastructure, was quoted as saying in a statement.

Meta signs multibillion-dollar deal to use Amazon's Graviton chips for agentic AI

Facebook parent Meta signed a deal to use Amazon's Graviton chips for agentic AI, the latest indication of growing demand for the tech giant's growing silicon business. Bloomberg reports that the deal is worth billions of dollars over multiple years. It comes one day after Meta said it would lay off roughly 10% of its workforce, or about 8,000 employees, as companies across the industry cut headcount while pouring billions into AI infrastructure. The deal gives Meta access to tens of millions of Graviton5 processor cores, running in AWS data centers, making Meta one of the largest Graviton customers in the world, the companies said. It builds on Meta's existing use of Amazon Bedrock, the company's platform for AI models. Amazon CEO Andy Jassy said in a LinkedIn post that agentic AI is "becoming almost as big a CPU story as a GPU story." In other words, while graphical processing units (mostly from Nvidia) have dominated the AI hardware conversation, agentic systems need traditional central processing units to handle the reasoning and coordination that happens between steps. Meta has taken a broad approach, signing deals with Nvidia and AMD, recently agreeing to use Google's custom processors, and developing its own in-house silicon with Broadcom. "As we scale the infrastructure behind Meta's AI ambitions, diversifying our compute sources is a strategic imperative," said Santosh Janardhan, head of infrastructure at Meta, in a release. Amazon is establishing itself as a major chipmaker in its own right. CEO Andy Jassy disclosed in his annual shareholder letter that Amazon's custom silicon business is generating more than $20 billion a year in revenue, saying it's "quite possible" Amazon will sell racks of its chips to third parties in the future. That would mean competing more directly with Nividia. Its roster of chip customers is growing. Anthropic committed to running its models on Amazon's Trainium processors as part of a $25 billion expanded partnership announced this week, and OpenAI agreed to use Trainium as part of a $100 billion cloud deal earlier this year.

Meta picks Amazon's 3nm Graviton chips to power next AI wave

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.

Meta inks deal to use more Amazon chips

Why it matters: The move comes as the leading cloud providers, including Amazon, aim to increase adoption of their homegrown chips amid an industrywide shortage of Nvidia graphics chips. Driving the news: The companies said Amazon will initially provide Meta with tens of millions of Graviton cores, with the potential to expand even further. * The new pact, which builds on an existing partnership between AWS and Meta, will make Meta one of the largest users of Graviton chips, the companies said. What they're saying: "The deal reflects a shift in how AI infrastructure gets built," the companies said in a statement. * "While GPUs remain essential for training large models, the rise of agentic AI is creating massive demand for CPU-intensive workloads -- real-time reasoning, code generation, search, and orchestrating multi-step tasks." The big picture: Google is also trying to boost adoption of its Tensor chips. On Wednesday the company announced its eighth-generation TPUs, including separate versions for training and inference.

Meta Agrees to Deploy Millions of Amazon AI Chips in Deal Worth Billions - Decrypt

AWS VP Nafea Bshara said the multi-year deal would be worth billions of dollars. Social media giant Meta signed an agreement with Amazon Web Services to deploy tens of millions of Graviton5 processors for its next-generation AI infrastructure, making the company one of AWS's largest Graviton customers globally. The partnership spans three to five years and will be worth billions of dollars, AWS Vice President Nafea Bshara told Reuters. Meta will deploy Amazon's fifth-generation CPU processors, which are purpose-built for agentic AI workloads -- applications that can reason, generate code, and orchestrate multi-step tasks independently. Each Graviton5 chip contains 192 cores that can be assigned to different tasks simultaneously, enabling parallel processing for complex AI workflows. "As we scale the infrastructure behind Meta's AI ambitions, diversifying our compute sources is a strategic imperative," said Meta Head of Infrastructure Santosh Janardhan, 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." The deal underscores how major technology companies are expanding beyond graphics processors that have dominated AI model training. As AI applications mature from research to production, companies increasingly need CPUs optimized for running trained models efficiently -- handling user queries, generating responses, and managing complex reasoning tasks in real time. The deal comes one day after Meta, the parent company behind Facebook and Instagram, confirmed reports of mass layoffs, with 8,000 jobs to be cut and 6,000 open positions to remain unfilled. The shift comes as Meta increasingly positions AI as its north star and attempts to compete with powerful rivals like OpenAI, Anthropic, and Google.

AWS inks multibillion-dollar AI infrastructure deal with Meta - SiliconANGLE

AWS inks multibillion-dollar AI infrastructure deal with Meta Amazon Web Services Inc. has inked a multiyear deal to supply Meta Platforms Inc. with cloud infrastructure. Bloomberg reported today that the agreement is worth billions of dollars. The deal centers on AWS' Graviton family of internally-developed central processing units. According to the company, Meta will purchase access to tens of millions of Graviton cores with the option to add more down the line. It will use the chips to power artificial intelligence agents. AWS debuted the newest addition to the Graviton chip line, the Graviton5, last December. It features 192 cores made using a 3-nanometer manufacturing process. The cores implement Arm Holdings plc's ubiquitous instruction set architecture, or ISA. A chip's ISA defines the language in which it expresses computations. The "words" that make up the language are simple computing operations such as arithmetic calculations. Arm's ISA also includes matrix and vector extensions, computations optimized for AI workloads. AWS says that Graviton5 is 25% faster than its previous custom CPU. One of the contributors to the chip's speed is that its L3 cache is 5 times larger. An L3 cache is a memory pool that keeps bits immediately next to a processor's cores. Shortening the distance between two sets of circuits reduces the amount of time it takes data to travel between them, which speeds up processing. CPUs perform a wide range of tasks in AI clusters. They coordinate the graphics cards that perform the bulk of the calculations involved in running a neural network. Additionally, AI agents like those Meta plans to run on Graviton5 can use CPUs to power their tools. Those are the third-party applications an agent uses to automate tasks. Graviton5 is designed to work with a collection of hardware and software modules called the AWS Nitro System. It offsets certain infrastructure management tasks from CPUs to specialized accelerators, which leaves more computing capacity for customer applications. Public cloud operators often use a single set of infrastructure assets to power multiple customers' workloads. Those workloads are isolated from one another to minimize cybersecurity risks. According to AWS, Graviton5 uses a module called the Nitro Isolation Engine to verify that different users' workloads are indeed isolated from one another. "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 Meta head of infrastructure Santosh Janardhan.

Meta strikes deal with Amazon's cloud unit to use its CPU chips - The Economic Times

Meta will ⁠use "tens of ⁠millions of cores" worth of Graviton chips. Each chip itself contains 192 cores, but they can each be assigned to different tasks.Meta Platforms and Amazon.com on Friday said Meta will use Amazon Web Services' (AWS) Graviton5 central processing unit (CPU) chips, a deal an AWS executive told Reuters would span multiple years and be worth billions of dollars. Meta will ⁠use "tens of ⁠millions of cores" worth of Graviton chips. Each chip itself contains 192 cores, but they can each be assigned to different tasks. While graphics processing units (GPUs) made by firms such as Nvidia remain essential for training AI models, once they are trained and deployed they ⁠often run on CPUs. The CPU market is undergoing an AI-driven renaissance, with Intel saying this week ⁠CPU prices were rising as demand soars. AWS has been developing its in-house CPU since 2018 and is now on its fifth generation of the chip, which it buys directly from Taiwan Semiconductor Manufacturing Co. "We pass that savings on to the customers," Nafea Bshara, vice president and distinguished engineer at Amazon Web Services, told Reuters, saying the Meta deal would span multiple years and be worth billions of dollars. ⁠Meta has previously signed large chip deals with Nvidia and Advanced Micro Devices, and also has worked closely with Arm Holdings on Arm's new CPU. "As we scale the infrastructure behind Meta's AI ambitions, diversifying our compute sources is a strategic imperative," Santosh Janardhan, head of infrastructure at Meta, said in a statement.

Meta Is Adding Tens of Millions of AWS Graviton Cores To Its Compute Portfolio As Agentic AI Becomes "Almost As Big a CPU Story As A GPU Story"

Meta has partnered with Amazon's AWS to bring tens of millions of Graviton CPU cores to its AI compute portfolio for Agentic AI. As the Agentic AI era rages on, companies are rapidly expanding their AI infrastructure to meet rising compute demands. We have seen multi-GigaWatt deals being signed here and there, and CPU usage is on the rise. With all of this happening, Meta has also announced its blockbuster partnership with Amazon's AWS. The new partnership centers around AWS's Graviton CPUs, which Meta will be using for its compute portfolio. In the announcement, Meta says that they will be adding "Tens of Millions" of AWS Graviton CPUs. That's a huge number of CPUs since each of the latest Graviton5 chip packs 192 Arm Neoverse cores. The following are some of the key highlights of the partnership: With this, Meta will become one of Amazon's largest Graviton customers across the globe. And the use of Graviton chips also showcases just how much essential CPUs have become for Agentic AI. CPU makers are seeing massive adoption and interest in their products. Intel, AMD, NVIDIA, Amazon, essentially every firm that makes a CPU is now being approached by AI firms to gain access to as many chips as possible. "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 purposebuilt silicon with the full AWS AI stack to power the next generation of agentic AI." - Nafea Bshara, Vice President and Distinguished Engineer, Amazon At the same time, AI firms are also preparing their own custom silicon, which will be used for AI. Meta has already partnered with Broadcom on the development of custom AI silicon, which will be used to power a "Multi-Gigawatt" ecosystem. Meta already produces several MITA series accelerators, but with chipmakers such as TSMC, Samsung, and the rest being severely constrained, the next possible route is to go to chip makers who are already producing chips at these semiconductor firms, or just knock on the door of cloud AI providers. And the "tens of millions of cores" is just the first deployment. Meta aims to aggressively scale up its AI resources in the coming years, so as the AI ecosystem expands, we will see even more chips being added.

Meta Becomes One of World's Largest Customers of Amazon AI Chips | PYMNTS.com

By completing this form, you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, if applicable, in accordance with our Privacy Policy and Terms and Conditions. The agreement with Amazon Web Services (AWS) will bring tens of millions of these cores into Meta's compute portfolio, with the flexibility to add more, Meta said in a Friday (April 24) press release. The agreement builds on the companies' longstanding relationship and supports Meta's broader goal of diversifying compute to meet the demands of its AI systems, according to the release. "As we scale the infrastructure behind Meta's AI ambitions, diversifying our compute sources is a strategic imperative," Meta Head of Infrastructure Santosh Janardhan said in the release. "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." This announcement came a day after it was reported that Meta plans to lay off about 8,000 employees, or 10% of its workforce, and leave 6,000 open roles unfilled to offset the investments it has been making in AI infrastructure. PYMNTS reported in March that Meta plans to spend between $115 billion and $135 billion this year as it races to construct data centers, chips and other AI infrastructure. This level of spending puts it in the company of some of the biggest investors in AI infrastructure, including Amazon, Google and Microsoft. AWS announced the agreement in its own Friday press release, saying that the deal builds on Meta's longstanding relationship with AWS and use of Amazon Bedrock, a platform for building generative AI applications and agents, at scale to support its AI. The company added that purpose-built chips such as Graviton are the most efficient way to power agentic workloads like code generation, real-time reasoning and frontier model training. "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," Nafea Bshara, vice president and distinguished engineer at Amazon, said in the release. Amazon CEO Andy Jassy said in a 2025 Letter to Shareholders posted April 9 that Amazon's chips business will be much larger than most people think. The company's annual revenue run rate for its chips business, which includes Graviton, Trainium and Nitro, is over $20 billion and growing triple-digit percentages year over year. "If our chips business was a stand-alone business, and sold chips produced this year to AWS and other third parties (as other leading chips companies do), our annual run rate would be ~$50 billion," Jassy said.

Meta expands AWS partnership with large-scale deployment of graviton processors

Meta has finalized an agreement to deploy AWS Graviton processors at scale, marking a substantial expansion of its long-standing partnership with Amazon Web Services (AWS). The initial deployment will encompass tens of millions of Graviton cores, with provisions to scale further as Meta develops its next-generation artificial intelligence (AI) infrastructure. This agreement highlights a broader industry shift in how AI infrastructure is architected, balancing the established use of hardware alongside newly optimized processors for emerging workloads. While Graphics Processing Units (GPUs) remain foundational for training large AI models, the increasing prevalence of agentic AI -- autonomous systems designed to reason, plan, and execute complex workflows -- is generating massive demand for CPU-intensive infrastructure. Meta is utilizing the Graviton deployment to support these specific agentic workloads, which include: Purpose-built processors are currently viewed as the most efficient method for powering these CPU-bound operations at scale. To meet the demands of its frontier models, Meta's infrastructure will rely heavily on the AWS Graviton5 processor. Engineered specifically for high-performance computing, the chips offer several structural upgrades over previous generations: As AI computation demands escalate globally, both cost management and environmental impact have become central to infrastructure planning. AWS Graviton5 processors are manufactured using 3-nanometer chip technology. This smaller, more precise manufacturing process inherently yields more efficient processors. Because AWS oversees the entire pipeline -- from fundamental chip design to server architecture integration -- the hardware can be heavily optimized compared to off-the-shelf alternatives. Consequently, Graviton5 delivers up to 25% better performance than the previous generation while maintaining leading energy efficiency. This allows organizations like Meta to scale their AI operations and deliver personalized experiences globally while remaining aligned with corporate sustainability targets. Commenting on this, Nafea Bshara, Vice President and Distinguished Engineer, Amazon, said: 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. Santosh Janardhan, Head of Infrastructure, Meta, said: