The c7g.16xlarge pairs 64 vCPU with 128 GiB of RAM, the 2.00 GiB-per-vCPU ratio that marks a compute-optimized instance. In the name, "c" stands for compute, "7" is the generation, "g" marks AWS Graviton (ARM) processors and "16xlarge" is the size within the c7g family. It runs on AWS Graviton3 Processor at 2.5 GHz, and AWS introduced it in May 2022. AWS has since shipped c8g and c9g; c8g.16xlarge is the direct replacement at this size, scoring 1,995,323 CoreMark/s against this instance's 1,611,786 — roughly 24% more throughput for the same vCPU count. Spot's node ladder tops out below this size, so c7g.16xlarge becomes 4 × ch.vs1.2xlarge (64 vCPU, 128 GiB combined), about 93% 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
c7g.16xlarge gives you 64 vCPU and 128 GiB in a single machine. The largest comparable Spot node, ch.vs1.2xlarge, is 16 vCPU and 32 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 128 GiB in one process, it does not.
x86_64 onlyc7g.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.
