Instances›AWS EC2›m6gd›m6gd.16xlarge
Compute
vCPUs64
Memory256 GiB
Mem / vCPU4.00 GiB
ProcessorGraviton2 Processor
Clock speed2.5 GHz
Architecturearm64
Storage
Type2 × 1,900 GB NVMe SSD
Bandwidth19,000 Mbps
Throughput2375 MB/s
IOPS80,000
Networking
Performance25 Gigabit
Max ENIs15
IPv6Yes
GPUNone
Family sizes
m6gd.medium1 vCPU · 4 GiB
m6gd.large2 vCPU · 8 GiB
m6gd.xlarge4 vCPU · 16 GiB
m6gd.2xlarge8 vCPU · 32 GiB
m6gd.4xlarge16 vCPU · 64 GiB
m6gd.8xlarge32 vCPU · 128 GiB
m6gd.12xlarge48 vCPU · 192 GiB
m6gd.16xlarge64 vCPU · 256 GiB
m6gd.metal64 vCPU · 256 GiB
m6gd.16xlarge

m6gd.16xlarge is AWS's general-purpose EC2 size at 64 vCPU and 256 GiB. In the name, "m" is the general-purpose line, "6" is the generation, "gd" marks AWS Graviton (ARM) processors and local NVMe storage and "16xlarge" is the size within the m6gd family. It runs on AWS Graviton2 Processor at 2.5 GHz, and AWS introduced it in July 2020. AWS has since shipped m7gd, m8gd and m9gd; m7gd.16xlarge is the direct replacement at this size, scoring 1,664,499 CoreMark/s against this instance's 1,289,110 — roughly 29% more throughput for the same vCPU count. The closest Spot shape is gp.vs2.2xlarge at 16 vCPU, so this instance maps to 4 of them — 64 vCPU and 256 GiB across the fleet, about 94% below the US East (N. Virginia) on-demand rate. 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

m6gd.16xlarge gives you 64 vCPU and 256 GiB in a single machine. The largest comparable Spot node, gp.vs2.2xlarge, is 16 vCPU and 64 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 256 GiB in one process, it does not.

x86_64 onlym6gd.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.
No local diskm6gd.16xlarge comes with 2 × 1,900 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$2.893$1.095$1.823$1.250$0.164
$2.729 savings
US Central, Chicagono AWS region$0.164
US Central, Dallasno AWS region$0.204
Hong Kong$3.968$2.500$1.714$0.044
$3.924 savings
Sydney, Australia$3.648$1.105$2.285$1.555$0.644
$3.004 savings
London, UK$3.354$0.620$2.113$1.449$0.884
$2.470 savings
US West, San Jose$3.392$0.612$2.151$1.486$0.604
$2.788 savings
US Central, Dallas 2no AWS region$0.004
US East, N. Virginia 2$2.893$1.095$1.823$1.250$0.604
$2.289 savings
When to use it
Good for
  • ●Web and application servers with mixed CPU and memory demand
  • ●Microservices and container fleets
  • ●Development, staging and CI environments
  • ●Workloads that fit inside 256 GiB of RAM
  • ●Jobs that want 2 × 1,900 GB of local NVMe scratch space
  • ●Network-heavy services — AWS rates this size at 25 Gigabit
  • ●Anything that shards cleanly across 4 nodes, which is how it maps onto Rackspace Spot
Avoid if
  • ●Starting a new deployment. m7gd.16xlarge is the newer generation at this size.
  • ●The working set needs more than 256 GiB of RAM
  • ●You cannot rebuild x86-only binaries or vendor images for aarch64
  • ●The work is single-threaded. Most of these 64 vCPU would sit idle.
  • ●GPU or FPGA acceleration is needed
  • ●Sustained full-core CPU load. A compute-optimized family costs less per unit of work.
m6gd.16xlarge runs $2,112/mo on AWS on-demand. The 4-node equivalent on Rackspace Spot: $120/mo.
  • 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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