According to AWS:

  • Graviton4 (pictured at left; credit: Business Wire) provides up to 30 percent better compute performance, 50 percent more cores and 75 percent more memory bandwidth than current generation Graviton3 processors, delivering the best price performance and energy efficiency for a broad range of workloads running on Amazon EC2.
  • Trainium2 (prototype pictured at right; credit: Business Wire) is designed to deliver up to 4x faster training than first generation Trainium chips and will be deployed in EC2 UltraClusters of up to 100,000 chips, making it possible to train foundation models (FMs) and large language models (LLMs) in a fraction of the time, while improving energy efficiency up to 2x.

AWS said it offers more than 150 different Graviton-powered Amazon EC2 instance types at scale, has built more than 2 million Graviton processors, and has more than 50,000 customers—including the top 100 EC2 customers—using Graviton-based instances. Customers including Datadog, DirecTV, Discovery, Formula 1 (F1), NextRoll, Nielsen, Pinterest, SAP, Snowflake, Sprinklr, Stripe, and Zendesk.

AWS said Graviton4 will be available in memory-optimized Amazon EC2 R8g instances, enabling customers to improve the execution of their high-performance databases, in-memory caches, and big data analytics workloads. R8g instances offer larger instance sizes with up to 3x more vCPUs and 3x more memory than current generation R7g instances. This allows customers to process larger amounts of data, scale their workloads, improve time-to-results, and lower their total cost of ownership. Graviton4-powered R8g instances are available today in preview, with general availability planned in the coming months. To learn more about Graviton4-based R8g instances, visit

The company said Trainium2 will be available in Amazon EC2 Trn2 instances, containing 16 Trainium chips in a single instance. Trn2 instances are intended to enable customers to scale up to 100,000 Trainium2 chips in next generation EC2 UltraClusters, interconnected with AWS Elastic Fabric Adapter (EFA) petabit-scale networking, delivering up to 65 exaflops of compute and giving customers on-demand access to supercomputer-class performance. With this level of scale, customers can train a 300-billion parameter LLM in weeks versus months.

“With each successive generation of chip, AWS delivers better price performance and energy efficiency, giving customers even more options—in addition to chip/instance combinations featuring the latest chips from third parties like AMD, Intel and NVIDIA—to run virtually any application or workload on Amazon Elastic Compute Cloud (Amazon EC2),” AWS said in its announcement.

“Silicon underpins every customer workload, making it a critical area of innovation for AWS,” said David Brown, vice president of Compute and Networking at AWS. “By focusing our chip designs on real workloads that matter to customers, we’re able to deliver the most advanced cloud infrastructure to them. Graviton4 marks the fourth generation we’ve delivered in just five years, and is the most powerful and energy efficient chip we have ever built for a broad range of workloads. And with the surge of interest in generative AI, Tranium2 will help customers train their ML models faster, at a lower cost, and with better energy efficiency.”

A leading advocate for the responsible deployment of generative AI, Anthropic is an AI safety and research company that creates reliable, interpretable, and steerable AI systems. An AWS customer since 2021, Anthropic recently launched Claude–an AI assistant focused on being helpful, harmless, and honest. “Since launching on Amazon Bedrock, Claude has seen rapid adoption from AWS customers,” said Tom Brown, co-founder of Anthropic. “We are working closely with AWS to develop our future foundation models using Trainium chips. Trainium2 will help us build and train models at a very large scale, and we expect it to be at least 4x faster than first generation Trainium chips for some of our key workloads. Our collaboration with AWS will help organizations of all sizes unlock new possibilities, as they use Anthropic’s state-of-the-art AI systems together with AWS’s secure, reliable cloud technology.”

More than 10,000 organizations worldwide—including Comcast, Condé Nast, and over 50 percent of the Fortune 500—rely on Databricks to unify their data, analytics, and AI. “Thousands of customers have implemented Databricks on AWS, giving them the ability to use MosaicML to pre-train, finetune, and serve FMs for a variety of use cases,” said Naveen Rao, vice president of Generative AI at Databricks. “AWS Trainium gives us the scale and high performance needed to train our Mosaic MPT models, and at a low cost. As we train our next generation Mosaic MPT models, Trainium2 will make it possible to build models even faster, allowing us to provide our customers unprecedented scale and performance so they can bring their own generative AI applications to market more rapidly.”

Datadog is an observability and security platform that provides full visibility across organizations. “At Datadog, we run tens of thousands of nodes, so balancing performance and cost effectiveness is extremely important. That’s why we already run half of our Amazon EC2 fleet on Graviton,” said Laurent Bernaille, principal engineer at Datadog. “Integrating Graviton4-based instances into our environment was seamless, and gave us an immediate performance boost out of the box, and we’re looking forward to using Graviton4 when it becomes generally available.”

Honeycomb is the observability platform that enables engineering teams to find and solve problems they couldn’t before. “We are thrilled to have evaluated AWS Graviton4-based R8g instances,” said Liz Fong-Jones, Field CTO at Honeycomb. “In recent tests, our Go-based OpenTelemetry data ingestion workload required 25 percent fewer replicas on the Graviton4-based R8g instances compared to Graviton3-based C7g/M7g/R7g instances—and additionally achieved a 20% improvement in median latency and 10% improvement in 99th percentile latency. We look forward to leveraging Graviton4-based instances once they become generally available.”

SAP HANA Cloud, SAP’s cloud-native in-memory database, is the data management foundation of SAP Business Technology Platform (SAP BTP). “Customers rely on SAP HANA Cloud to run their mission-critical business processes and next-generation intelligent data applications in the cloud,” said Juergen Mueller, CTO and member of the Executive Board of SAP SE. “As part of the migration process of SAP HANA Cloud to AWS Graviton-based Amazon EC2 instances, we have already seen up to 35 percent better price performance for analytical workloads. In the coming months, we look forward to validating Graviton4, and the benefits it can bring to our joint customers.”