AWS r5a.16xlargevsAWS r5a.2xlarge

r5a.16xlarge pairs 64 vCPUs with 512GB of RAM at $3.6160/hr On-Demand (about $2604/mo at 24×7). r5a.2xlarge pairs 8 vCPUs with 64GB at $0.4520/hr (~$325/mo). r5a.2xlarge is 87% cheaper per hour than r5a.16xlarge ($3.1640/hr gap).

Because both instances are in the **r5a family**, the only thing that changes between them is sizing — same silicon, same architecture (AMD EPYC (x86_64)), same burstable/sustained behavior. The choice is purely about how much capacity you actually need: r5a.16xlarge gives you 64 vCPUs and 512GB of RAM, r5a.2xlarge gives you 8 vCPUs and 64GB. AWS scales pricing close to linearly within a family, so picking the right size is mostly about right-sizing your workload, not getting a better deal per vCPU.

On raw price-per-performance, the two are r5a.2xlarge delivers ~698% more single-thread Sysbench score per dollar (350 vs 2794 points per $1/hr). That's the cleanest signal we have for "which one runs your workload faster per dollar," but it only matters if your workload is single-thread-bound; for parallel workloads the multi-core scores (42013 vs 5237) are what to weigh. Spot pricing flips many of these comparisons — when r5a.16xlarge drops to $0.8292/hr and r5a.2xlarge drops to $0.1916/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick r5a.16xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r5a.2xlarge when it's closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). When neither side is obviously right, the cheaper hourly rate usually wins for fault-tolerant batch workloads, while the higher single-core score usually wins for latency-sensitive web traffic. The regional pricing tables linked from each instance page below show where each is currently cheapest — sometimes a >20% regional gap flips the comparison entirely.