Why AWS Graviton4 instances matter for European cloud hosting costs

The AWS Europe (Paris) region now includes Amazon EC2 C8gn instances. These instances use Graviton4 processors. I see a 30% compute performance improvement over the Graviton3-based C7gn instances. The C8gn family includes 6th generation AWS Nitro Cards. These instances provide up to 600 Gbps network bandwidth. This bandwidth is the highest among network optimized EC2 instances. The C8gn instances provide sizes up to 48xlarge and up to 384 GiB of memory. They also provide up to 120 Gbps of bandwidth to Amazon Elastic Block Store. For workloads in tightly coupled clusters, EFA networking is available on 16xlarge, 24xlarge, 48xlarge, metal-24xl, and metal-48xl sizes. This is useful for data analytics and CPU-based AI/ML inference. The R8g instances provide an 8:1 memory-to-vCPU ratio and provide up to 3x more vCPUs and 3x more memory than current generation R7g instances.

The math of price-performance

I look at the price-performance ratio. Graviton4 provides up to 29% better price-performance than Graviton3. The architectural move from Graviton3 to Graviton4 is a fundamental redesign. Graviton4 runs on the Neoverse V2 architecture and uses DDR5-5600 memory. For large Java applications, performance increases by up to 45%. On Amazon RDS, Graviton4 provides higher transaction throughput and query execution speeds. For video encoding, Graviton4 provides a 12% performance gain over Graviton3.

I see the cost.

The math is simple.

If you run a web application stack with three app servers and a database, switching from Intel to Graviton can save you $2,580 per year without any architecture changes or code rewrites. Because AWS designs the core and contracts fabrication through TSMC, the company collapses the stack and avoids the external vendor margin that Intel and AMD require to make a profit. Graviton instances cost 20% less per hour than Intel equivalents. For example, a m7g.xlarge costs $0.1456 per hour while the m7i.xlarge costs $0.1814 per hour.

The newest Graviton5 chip arrives with M9g and M9gd instances. This chip became available on June 10, 2026. It provides 25% better compute performance. This chip includes a 192-core, four-chiplet design with an L3 cache five times larger than Graviton4. It uses DDR5-8800 memory.

Total cost of ownership calculation includes infrastructure, support, software licensing, data storage, and network bandwidth. It also includes personnel expenses, data transfer charges, and security controls. For example, data transfer fees often continue after migration for hybrid architectures or multi-region designs. AWS provides 100 GB of free data transfer out to the internet each month. For EKS or ECS, users use ARM64 node groups. For Lambda, users change the architecture parameter to arm64 to get up to 34% better price-performance.

The migration reality

I find the lack of Windows support a major flaw. Graviton does not support Windows. If your workload requires Windows Server, you cannot use Graviton. This limitation is absolute. Many companies also run x86-specific software like Oracle Database. These users cannot migrate to Graviton without code changes or replacing the software.

You already know how to manage Linux. Most modern languages like Go, Python, Node.js, and Java support ARM64 natively. The migration process follows four specific phases: assessment, software review, configuration, and rollout, where Phase 1 covers assessment and Phase 2 covers software review. Phase 3 covers environment configuration and Phase 4 covers staged rollout. The timeline spans 12 weeks. Weeks 1 and 2 involve assessment, and weeks 3 and 4 involve preparation. Weeks 5 through 8 cover testing. Weeks 9 through 12 involve production migration.

For containerized workloads, you must use the Docker buildx feature to build multi-architecture images. For RDS, simply change the instance type during the scheduled maintenance window. Change the Lambda architecture to arm64. You use ARM64 node groups for EKS or ECS. A blue/green deployment involves launching new Graviton instances behind the load balancer and shifting traffic gradually.

The migration takes time.

Will the cost savings of Graviton4 persist as more vendors release ARM chips?