Instances›AWS EC2›m6gd›m6gd.8xlarge
Compute
vCPUs32
Memory128 GiB
Mem / vCPU4.00 GiB
ProcessorGraviton2 Processor
Clock speed2.5 GHz
Architecturearm64
Storage
Type1 × 1,900 GB NVMe SSD
Bandwidth9,500 Mbps
Throughput1187.5 MB/s
IOPS40,000
Networking
Performance12 Gigabit
Max ENIs8
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.8xlarge

The m6gd.8xlarge pairs 32 vCPU with 128 GiB of RAM, the 4.00 GiB-per-vCPU ratio that marks a general-purpose instance. In the name, "m" is the general-purpose line, "6" is the generation, "gd" marks AWS Graviton (ARM) processors and local NVMe storage and "8xlarge" 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.8xlarge is the direct replacement at this size, scoring 817,160 CoreMark/s against this instance's 608,789 — roughly 34% more throughput for the same vCPU count. Spot's node ladder tops out below this size, so m6gd.8xlarge becomes 2 × gp.vs2.2xlarge (32 vCPU, 128 GiB combined), 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.8xlarge gives you 32 vCPU and 128 GiB in a single machine. The largest comparable Spot node, gp.vs2.2xlarge, is 16 vCPU and 64 GiB, so the equivalent here is 2 nodes rather than one.

Spot runs as managed Kubernetes, so a 2-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 32 cores and 128 GiB in one process, it does not.

x86_64 onlym6gd.8xlarge 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.8xlarge comes with 1 × 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$1.446$0.469$0.911$0.625$0.082
$1.364 savings
US Central, Chicagono AWS region$0.082
US Central, Dallasno AWS region$0.102
Hong Kong$1.984$1.250$0.857$0.022
$1.962 savings
Sydney, Australia$1.824$0.645$1.142$0.777$0.322
$1.502 savings
London, UK$1.677$0.444$1.056$0.724$0.442
$1.235 savings
US West, San Jose$1.696$0.463$1.075$0.743$0.302
$1.394 savings
US Central, Dallas 2no AWS region$0.002
US East, N. Virginia 2$1.446$0.469$0.911$0.625$0.302
$1.144 savings
When to use it
Good for
  • ●Microservices and container fleets
  • ●Development, staging and CI environments
  • ●Small to mid-size relational databases
  • ●Workloads that fit inside 128 GiB of RAM
  • ●Jobs that want 1 × 1,900 GB of local NVMe scratch space
  • ●Network-heavy services — AWS rates this size at 12 Gigabit
  • ●Anything that shards cleanly across 2 nodes, which is how it maps onto Rackspace Spot
Avoid if
  • ●Starting a new deployment. m7gd.8xlarge is the newer generation at this size.
  • ●The working set needs more than 128 GiB of RAM
  • ●You cannot rebuild x86-only binaries or vendor images for aarch64
  • ●GPU or FPGA acceleration is needed
  • ●Sustained full-core CPU load. A compute-optimized family costs less per unit of work.
  • ●More than 4.00 GiB of RAM per vCPU is needed — that ratio is fixed for the whole family
Stop overpaying AWS. This compute costs $1,056/mo on AWS vs $60/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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