AWS r5a.12xlargevsAWS r5a.4xlarge

r5a.12xlarge pairs 48 vCPUs with 384GB of RAM at $2.7120/hr On-Demand (about $1953/mo at 24×7). r5a.4xlarge pairs 16 vCPUs with 128GB at $0.9040/hr (~$651/mo). r5a.4xlarge is 67% cheaper per hour than r5a.12xlarge ($1.8080/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.12xlarge gives you 48 vCPUs and 384GB of RAM, r5a.4xlarge gives you 16 vCPUs and 128GB. 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.4xlarge delivers ~202% more single-thread Sysbench score per dollar (464 vs 1399 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 (31446 vs 10501) are what to weigh. Spot pricing flips many of these comparisons — when r5a.12xlarge drops to $1.0527/hr and r5a.4xlarge drops to $0.3424/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick r5a.12xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r5a.4xlarge 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.