AWS r5d.12xlargevsAWS r5d.16xlarge

r5d.12xlarge pairs 48 vCPUs with 384GB of RAM at $3.4560/hr On-Demand (about $2488/mo at 24×7). r5d.16xlarge pairs 64 vCPUs with 512GB at $4.6080/hr (~$3318/mo). r5d.12xlarge is 33% cheaper per hour than r5d.16xlarge ($1.1520/hr gap).

Because both instances are in the **r5d family**, the only thing that changes between them is sizing — same silicon, same architecture (Intel Xeon (x86_64)), same burstable/sustained behavior. The choice is purely about how much capacity you actually need: r5d.12xlarge gives you 48 vCPUs and 384GB of RAM, r5d.16xlarge gives you 64 vCPUs and 512GB. 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 r5d.12xlarge delivers ~43% more single-thread Sysbench score per dollar (328 vs 230 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 (39258 vs 51642) are what to weigh. Spot pricing flips many of these comparisons — when r5d.12xlarge drops to $1.2253/hr and r5d.16xlarge drops to $1.3376/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick r5d.12xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r5d.16xlarge 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.