AWS recently shipped M9g and M9gd instances, doubling the core count to 192 per chip and packing them onto four chiplets fabbed on TSMC's 3nm node. The spec provides: 192 MB of L3 cache (five times Graviton4), DDR5-8800 (the fastest DDR5 in any cloud instance), PCIe Gen 6, and the first formally verified hypervisor isolation in a production cloud environment.
AWS positions Graviton5 squarely at agentic AI workloads. The About Amazon blog describes it as "purpose-built for the demands of agentic AI, real-time reasoning, code generation, and multi-step task orchestration, where processors must handle large numbers of concurrent environments and keep accelerators moving."
Not everyone is buying the framing. On Reddit, the r/hardware community pushed back on the AI positioning while praising the chip itself. One commenter was blunt:
They're normal ARM cores, which can do everything you normally use a CPU for, such as running a webserver or a database. The only reason those are AI cores is because somebody in marketing thinks that will sell better with the word AI attached.
Another grounded the value in what practitioners actually care about:
Graviton has been a great CPU from day 1. No SMT, you get a real core per vCPU, tons of L2 cache, and cost effective. New gen is just more and better.
The distinction matters. Graviton5 is a genuinely excellent general-purpose ARM processor that happens to work well for agent workloads because agents are CPU-intensive. Calling it an "AI chip" overstates what changed architecturally. What changed is core count, cache, memory bandwidth, and interconnect latency. Those improvements benefit databases, web servers, and batch processing just as much as they benefit agents.
The Meta commitment is the headline validation. Meta has signed on to deploy tens of millions of Graviton5 cores for its agentic AI efforts, making it one of the largest Graviton customers in the world. Uber and Snowflake are also deploying Graviton5 for their agentic workloads.
Customer benchmarks from the six-month preview period tell a concrete performance story. ClickHouse saw a 36% performance boost compared to M8g with zero code changes. Honeycomb achieved 36% better throughput per core compared to Graviton4, measured across a six-month A/B test of production observability workloads. HubSpot deployed M9g for MySQL databases and saw query duration drop by up to 60%. Denis Sheahan, a principal performance engineer at Airbnb, called them "some of the fastest EC2 instances we have ever tested."
The Nitro Isolation Engine deserves separate attention. Built into the sixth-generation Nitro System, it provides mathematically proven isolation between virtual machines through formal verification, a technique where the correctness of the isolation boundary is established by mathematical proof rather than testing alone. As The New Stack reported, this makes Graviton5 instances the first in a major public cloud to carry formally verified hypervisor isolation in production. For teams running multi-tenant workloads or evaluating where to execute untrusted agent code, the formally verified boundary is a stronger security guarantee than what any competing cloud instance type currently offers.
Pricing is published but requires context. DevelopersIO's analysis of on-demand rates in us-east-1 found that M9g instances are uniformly 9% more expensive than M8g across all sizes. Applied against the 25% compute performance improvement, that translates to roughly 15% better price-performance per dollar. Actual gains will vary by workload. M9gd instances add up to 11.4 TB of NVMe SSD storage with 30% higher IOPS than the previous generation, targeting workloads such as media processing, batch jobs, and applications needing fast local scratch space.
The family is not yet complete. Compute-optimized C9g and memory-optimized R9g variants are planned for later in 2026. Teams with the most demanding inference or analytics workloads may want to wait for C9g benchmarks before committing to a migration, since M9g is a general-purpose instance type and may not represent the ceiling of what Graviton5 can deliver in specialized configurations.
Google ships custom Axion processors for GKE, and Microsoft relies on ARM-based Cobalt 100. AWS is the furthest along in custom silicon adoption, with Graviton accounting for more than half of all new CPU capacity added over the past three years and the custom silicon business crossing a $20 billion annual run rate.
M9g and M9gd instances are available now via On-Demand, Savings Plans, Spot, Dedicated Instances, and Dedicated Hosts. Moreover, the instances are currently live in US East (N. Virginia, Ohio), US West (Oregon), and EU (Frankfurt).