Stock Markets June 10, 2026 11:13 AM

AWS Rolls Out Graviton5 for Agentic AI, Breathing New Performance into EC2 Instance Lineup

192-core Graviton5 chips go into general availability with M9g and M9gd instances; Meta, Uber and Snowflake among early deployers

By Priya Menon
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AWS has made its Graviton5 processor generally available for all customers, positioning the 192-core chip to accelerate agentic AI workloads with up to 25% better compute versus the previous generation. New EC2 M9g and M9gd instances, previewed at re:Invent 2025, are now accessible through standard adoption paths and include higher memory, storage and I/O capabilities built on the sixth-generation Nitro System.

AWS Rolls Out Graviton5 for Agentic AI, Breathing New Performance into EC2 Instance Lineup
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Key Points

  • Graviton5 is now generally available and offers up to 25% better compute performance for agentic AI workloads compared with the previous generation.
  • M9g instances target faster web applications, machine learning inference and databases (35%, 35%, and 30% improvements respectively); M9gd adds up to 11.4 TB NVMe SSD and 30% higher IOPS.
  • Major customers including Meta, Uber and Snowflake are deploying Graviton cores; AWS reports over 120,000 customers building on the platform, and the instances run on the sixth-generation Nitro System with mathematically proven VM isolation.

AWS has opened general availability for its Graviton5 processor, offering customers a next-generation Arm-based chip designed specifically for agentic AI workloads. AWS states the chip provides up to 25% improved compute performance relative to the prior generation and features 192 cores per processor with 33% lower inter-core latency.

The Graviton5 is intended to support real-time reasoning, code generation and multi-step task orchestration. AWS has made EC2 instances powered by Graviton5 available: the M9g and M9gd families, which were first shown in a preview at re:Invent 2025 and are now accessible through standard EC2 adoption paths.

Several major customers have already begun deploying at scale. Meta has committed to using tens of millions of Graviton cores for its agentic AI efforts since the preview period. Other enterprise users including Uber and Snowflake are also deploying Graviton for agentic workloads, joining more than 120,000 customers who AWS says are building on the platform.

On measured workload comparisons provided by AWS, the M9g instances are positioned to deliver specific gains: 35% faster web applications, 35% faster machine learning inference and 30% faster databases versus the previous generation. The M9gd variant adds expanded local storage, offering up to 11.4 TB of NVMe SSD capacity along with up to 30% higher input/output operations per second than its predecessor.

Both instance types leverage the sixth-generation AWS Nitro System. Included in that platform is the Nitro Isolation Engine, which AWS describes as providing mathematically proven isolation between virtual machines. The Graviton5 platform supports DDR5-8800 memory speeds and PCIe Gen 6 connectivity.

For cloud customers and enterprise IT teams, the combination of higher core counts, reduced latency and increased local storage/I/O on the M9g and M9gd families represents a set of configuration choices meant to match a range of agentic AI and latency-sensitive workloads. The instances are now available through established EC2 channels for customers planning migrations or new deployments.


Technical details and availability

  • Processor: 192 cores per Graviton5 processor
  • Latency: 33% lower inter-core latency versus prior generation
  • Performance: Up to 25% better compute performance for agentic AI workloads
  • Memory and bus: Supports DDR5-8800 and PCIe Gen 6
  • Instances: M9g (compute/memory balance) and M9gd (includes NVMe SSDs up to 11.4 TB)
  • Platform: Sixth-generation AWS Nitro System with Nitro Isolation Engine

Adoption and customers

Meta, Uber and Snowflake are cited by AWS as early deployers, and the company reports that more than 120,000 customers are already building on the Graviton platform. M9g and M9gd instances move from preview to general availability and can be adopted through the standard EC2 provisioning paths.

Risks

  • Adoption concentration - several large customers are named (Meta, Uber, Snowflake), creating uncertainty about the pace and breadth of migration across the wider customer base; this impacts cloud providers and enterprise IT procurement.
  • Workload dependence - the performance percentages cited (web applications, ML inference, databases) are specific comparisons versus the prior generation, so actual gains will depend on individual workload characteristics; this affects software vendors and data-center operators.
  • Instance specialization - the M9gd's storage and IOPS advantages are tied to NVMe SSD configurations, meaning applications with different storage profiles may not realize the same benefits; this is relevant for data-intensive services and infrastructure planning.

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