Instances›AWS EC2›r9g›r9g.16xlarge
Compute
vCPUs64
Memory512 GiB
Mem / vCPU8.00 GiB
ProcessorGraviton5 Processor
Clock speed3.3 GHz
Architecturearm64
Storage
TypeEBS only
Bandwidth24,000 Mbps
Throughput3000 MB/s
IOPS96,000
Networking
Performance34 Gigabit
Max ENIs16
IPv6Yes
GPUNone
Family sizes
r9g.medium1 vCPU · 8 GiB
r9g.large2 vCPU · 16 GiB
r9g.xlarge4 vCPU · 32 GiB
r9g.2xlarge8 vCPU · 64 GiB
r9g.4xlarge16 vCPU · 128 GiB
r9g.8xlarge32 vCPU · 256 GiB
r9g.12xlarge48 vCPU · 384 GiB
r9g.16xlarge64 vCPU · 512 GiB
r9g.24xlarge96 vCPU · 768 GiB
r9g.48xlarge192 vCPU · 1536 GiB
r9g.metal-48xl192 vCPU · 1536 GiB
r9g.16xlarge

r9g.16xlarge is AWS's memory-optimized EC2 size at 64 vCPU and 512 GiB. In the name, "r" stands for RAM, "9" is the generation, "g" marks AWS Graviton (ARM) processors and "16xlarge" is the size within the r9g family. It runs on AWS Graviton5 Processor at 3.3 GHz, and AWS introduced it in August 2026. r9g is the current generation of the r family, so there is no newer AWS size to migrate to. The closest Spot shape is mh.vs1.2xlarge at 16 vCPU, so this instance maps to 4 of them — 64 vCPU and 512 GiB across the fleet, $4.11/hr on AWS in US East (N. Virginia), from $0.084/hr on Rackspace Spot. Spot delivers compute as managed Kubernetes, so a node pool of that size is the native shape of the answer rather than a workaround — provided the workload scales horizontally.

Match qualityScale-out match

r9g.16xlarge gives you 64 vCPU and 512 GiB in a single machine. The largest comparable Spot node, mh.vs1.2xlarge, is 16 vCPU and 128 GiB, so the equivalent here is 4 nodes rather than one.

Spot runs as managed Kubernetes, so a 4-node pool is the normal way to run things rather than a workaround. If your workload already sits behind a load balancer, a queue or a scheduler, it spreads across them without changes. If it needs all 64 cores and 512 GiB in one process, it does not.

x86_64 onlyr9g.16xlarge is Graviton (arm64) and Rackspace Spot has no arm64 nodes, so you'd be moving to x86. You'll need x86 builds of your images, and per-core speed differs between the chips — worth testing before you decide how many nodes to run.
Pricing by region
1 hr
RegionAWS on-demandAWS Spot1-yr Reserved3-yr ReservedRackspace SpotYou save
US East, N. Virginia$4.109$1.126$0.084
$4.025 savings
US Central, Chicagono AWS region$0.084
US Central, Dallasno AWS region$0.524
Hong Kong$0.084
Sydney, Australia$0.084
London, UK$0.524
US West, San Jose$0.008
US Central, Dallas 2no AWS region$0.968
When to use it
Good for
  • ●Database instances that keep the working set in RAM
  • ●Graph and search workloads with large indexes
  • ●In-memory caches such as Redis and Memcached
  • ●Workloads that fit inside 512 GiB of RAM
  • ●Parallel work that can occupy 64 vCPU
  • ●Network-heavy services — AWS rates this size at 34 Gigabit
  • ●Anything that shards cleanly across 4 nodes, which is how it maps onto Rackspace Spot
Avoid if
  • ●The working set needs more than 512 GiB of RAM
  • ●You cannot rebuild x86-only binaries or vendor images for aarch64
  • ●GPU or FPGA acceleration is needed
  • ●CPU-bound work. You are paying for memory this workload will not use.
  • ●More than 8.00 GiB of RAM per vCPU is needed — that ratio is fixed for the whole family
  • ●The work is single-threaded. Most of these 64 vCPU would sit idle.
$3,000/mo on AWS on-demand against $61/mo on Rackspace Spot for the 4-node equivalent — market-priced, not list-priced.
  • Spot sells spare capacity at market prices. It is the cheapest compute on the internet.
  • Prices are set by supply and demand. You pay what the market decides.
  • Compute is delivered as fully managed Kubernetes. All infrastructure is taken care of.
  • Egress costs $0.01/GB after the free allowance. AWS charges $0.09/GB.
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