AWS r5a.4xlargevsAWS r5a.xlarge

r5a.4xlarge pairs 16 vCPUs with 128GB of RAM at $0.9040/hr On-Demand (about $651/mo at 24×7). r5a.xlarge pairs 4 vCPUs with 32GB at $0.2260/hr (~$163/mo). r5a.xlarge is 75% cheaper per hour than r5a.4xlarge ($0.6780/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.4xlarge gives you 16 vCPUs and 128GB of RAM, r5a.xlarge gives you 4 vCPUs and 32GB. 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.xlarge delivers ~300% more single-thread Sysbench score per dollar (1399 vs 5593 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 (10501 vs 2610) are what to weigh. Spot pricing flips many of these comparisons — when r5a.4xlarge drops to $0.3424/hr and r5a.xlarge drops to $0.0883/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick r5a.4xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r5a.xlarge 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.