AWS r5.4xlargevsAWS r6i.4xlarge

r5.4xlarge pairs 16 vCPUs with 128GB of RAM at $1.0080/hr On-Demand (about $726/mo at 24×7). r6i.4xlarge pairs 16 vCPUs with 128GB at $1.0080/hr (~$726/mo). Both are priced identically per hour on-demand.

These are different generations of the same series. **r6i.4xlarge** is the newer generation, and AWS's pattern across generations is fairly consistent: ~10–15% better single-thread, 15–30% better multi-core, and similar or modestly higher per-hour pricing — so the price/performance per dollar usually improves with each generation. **r5.4xlarge** is still available and still works (AWS doesn't retire instance types quickly), but for new workloads the newer generation is typically the better default unless you have a specific reason to pin to the older AMI or there's a meaningful regional pricing advantage today.

On raw price-per-performance, the two are r6i.4xlarge delivers ~172% more single-thread Sysbench score per dollar (1084 vs 2952 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 (13459 vs 24777) are what to weigh. Spot pricing flips many of these comparisons — when r5.4xlarge drops to $0.2749/hr and r6i.4xlarge drops to $0.4012/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick r5.4xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r6i.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.