AWS r5ad.24xlargevsAWS r5ad.xlarge

r5ad.24xlarge pairs 96 vCPUs with 768GB of RAM at $6.2880/hr On-Demand (about $4527/mo at 24×7). r5ad.xlarge pairs 4 vCPUs with 32GB at $0.2620/hr (~$189/mo). r5ad.xlarge is 96% cheaper per hour than r5ad.24xlarge ($6.0260/hr gap).

Because both instances are in the **r5ad 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: r5ad.24xlarge gives you 96 vCPUs and 768GB of RAM, r5ad.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.

Benchmark data for at least one of these instances is still being collected, so a direct performance-per-dollar comparison isn't possible yet. Sysbench scores are pending for r5ad.24xlarge and 1264/2612 for r5ad.xlarge. Check back as the benchmark queue completes — newer-generation instances typically score 10–30% higher on single-thread and 15–50% higher on multi-core vs the previous generation in the same series.

In practice, pick r5ad.24xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r5ad.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.