Instances›AWS EC2›r6gd›r6gd.12xlarge
Compute
vCPUs48
Memory384 GiB
Mem / vCPU8.00 GiB
ProcessorGraviton2 Processor
Clock speed2.5 GHz
Architecturearm64
Storage
Type2 × 1,425 GB NVMe SSD
Bandwidth14,250 Mbps
Throughput1781.25 MB/s
IOPS50,000
Networking
Performance20 Gigabit
Max ENIs8
IPv6Yes
GPUNone
Family sizes
r6gd.medium1 vCPU · 8 GiB
r6gd.large2 vCPU · 16 GiB
r6gd.xlarge4 vCPU · 32 GiB
r6gd.2xlarge8 vCPU · 64 GiB
r6gd.4xlarge16 vCPU · 128 GiB
r6gd.8xlarge32 vCPU · 256 GiB
r6gd.12xlarge48 vCPU · 384 GiB
r6gd.16xlarge64 vCPU · 512 GiB
r6gd.metal64 vCPU · 512 GiB
r6gd.12xlarge

The r6gd.12xlarge is a memory-optimized AWS EC2 instance: 48 vCPU and 384 GiB of memory, 8.00 GiB per vCPU. In the name, "r" stands for RAM, "6" is the generation, "gd" marks AWS Graviton (ARM) processors and local NVMe storage and "12xlarge" is the size within the r6gd family. It runs on AWS Graviton2 Processor at 2.5 GHz, and AWS introduced it in July 2020. AWS has since shipped r7gd, r8gd and r9gd; r7gd.12xlarge is the direct replacement at this size, scoring 1,239,589 CoreMark/s against this instance's 931,556 — roughly 33% more throughput for the same vCPU count. No single Spot node covers 48 vCPU and 384 GiB, so the equivalent is a fleet: 3 × mh.vs1.2xlarge, 48 vCPU and 384 GiB in total, $2.76/hr on AWS in US East (N. Virginia), from $0.063/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

r6gd.12xlarge gives you 48 vCPU and 384 GiB in a single machine. The largest comparable Spot node, mh.vs1.2xlarge, is 16 vCPU and 128 GiB, so the equivalent here is 3 nodes rather than one.

Spot runs as managed Kubernetes, so a 3-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 48 cores and 384 GiB in one process, it does not.

x86_64 onlyr6gd.12xlarge 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.
No local diskr6gd.12xlarge comes with 2 × 1,425 GB NVMe SSD attached to the machine. Spot nodes use network storage only, so that disk doesn't come with it. If you were using it as fast scratch space, you'd move to a persistent volume or object storage, which are slower to read.
Pricing by region
1 hr
RegionAWS on-demandAWS Spot1-yr Reserved3-yr ReservedRackspace SpotYou save
US East, N. Virginia$2.765$0.523$1.742$1.194$0.063
$2.702 savings
US Central, Chicagono AWS region$0.063
US Central, Dallasno AWS region$0.393
Hong Kong$0.063
Sydney, Australia$3.336$0.782$2.117$1.452$0.063
$3.273 savings
London, UK$3.245$0.481$2.044$1.402$0.393
$2.852 savings
US West, San Jose$3.120$0.840$1.966$1.348$0.006
$3.114 savings
US Central, Dallas 2no AWS region$0.726
When to use it
Good for
  • ●Graph and search workloads with large indexes
  • ●In-memory caches such as Redis and Memcached
  • ●Large JVM heaps and application servers that hold state
  • ●Workloads that fit inside 384 GiB of RAM
  • ●Jobs that want 2 × 1,425 GB of local NVMe scratch space
  • ●Network-heavy services — AWS rates this size at 20 Gigabit
  • ●Anything that shards cleanly across 3 nodes, which is how it maps onto Rackspace Spot
Avoid if
  • ●Starting a new deployment. r7gd.12xlarge is the newer generation at this size.
  • ●The working set needs more than 384 GiB of RAM
  • ●You cannot rebuild x86-only binaries or vendor images for aarch64
  • ●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 48 vCPU would sit idle.
Stop overpaying AWS. This compute costs $2,018/mo on AWS vs $46/mo on Rackspace Spot.
  • 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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