Instances›AWS EC2›m7g›m7g.8xlarge
Compute
vCPUs32
Memory128 GiB
Mem / vCPU4.00 GiB
ProcessorGraviton3 Processor
Clock speed2.5 GHz
Architecturearm64
Storage
TypeEBS only
Bandwidth10,000 Mbps
Throughput1250 MB/s
IOPS40,000
Networking
Performance15 Gigabit
Max ENIs8
IPv6Yes
GPUNone
Family sizes
m7g.medium1 vCPU · 4 GiB
m7g.large2 vCPU · 8 GiB
m7g.xlarge4 vCPU · 16 GiB
m7g.2xlarge8 vCPU · 32 GiB
m7g.4xlarge16 vCPU · 64 GiB
m7g.8xlarge32 vCPU · 128 GiB
m7g.12xlarge48 vCPU · 192 GiB
m7g.16xlarge64 vCPU · 256 GiB
m7g.metal64 vCPU · 256 GiB
m7g.8xlarge

The m7g.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, "7" is the generation, "g" marks AWS Graviton (ARM) processors and "8xlarge" is the size within the m7g family. It runs on AWS Graviton3 Processor at 2.5 GHz, and AWS introduced it in February 2023. AWS has since shipped m8g and m9g; m8g.8xlarge is the direct replacement at this size, scoring 928,815 CoreMark/s against this instance's 815,390 — roughly 14% more throughput for the same vCPU count. Spot's node ladder tops out below this size, so m7g.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

m7g.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 onlym7g.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.
Pricing by region
1 hr
RegionAWS on-demandAWS Spot1-yr Reserved3-yr ReservedRackspace SpotYou save
US East, N. Virginia$1.306$0.572$0.864$0.592$0.082
$1.224 savings
US Central, Chicagono AWS region$0.082
US Central, Dallasno AWS region$0.102
Hong Kong$1.795$1.188$0.814$0.022
$1.773 savings
Sydney, Australia$1.632$0.617$1.080$0.740$0.322
$1.310 savings
London, UK$1.510$0.231$0.997$0.686$0.442
$1.068 savings
US West, San Jose$1.523$0.606$1.005$0.694$0.302
$1.221 savings
US Central, Dallas 2no AWS region$0.002
US East, N. Virginia 2$1.306$0.572$0.864$0.592$0.302
$1.004 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
  • ●Parallel work that can occupy 32 vCPU
  • ●Network-heavy services — AWS rates this size at 15 Gigabit
  • ●Anything that shards cleanly across 2 nodes, which is how it maps onto Rackspace Spot
Avoid if
  • ●Starting a new deployment. m8g.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
  • ●More than 4.00 GiB of RAM per vCPU is needed — that ratio is fixed for the whole family
  • ●The work is single-threaded. Most of these 32 vCPU would sit idle.
  • ●Local NVMe or instance-store disk is a hard requirement
$953/mo on AWS on-demand against $60/mo on Rackspace Spot for the 2-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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