AWS r5n.8xlargevsAWS r5n.xlarge

r5n.8xlarge pairs 32 vCPUs with 256GB of RAM at $2.3840/hr On-Demand (about $1716/mo at 24×7). r5n.xlarge pairs 4 vCPUs with 32GB at $0.2980/hr (~$215/mo). r5n.xlarge is 87% cheaper per hour than r5n.8xlarge ($2.0860/hr gap).

Because both instances are in the **r5n 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: r5n.8xlarge gives you 32 vCPUs and 256GB of RAM, r5n.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 r5n.xlarge delivers ~699% more single-thread Sysbench score per dollar (458 vs 3661 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 (27017 vs 3276) are what to weigh. Spot pricing flips many of these comparisons — when r5n.8xlarge drops to $0.7218/hr and r5n.xlarge drops to $0.1425/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick r5n.8xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r5n.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.