AWS r5.4xlargevsAWS r6g.4xlarge
r5.4xlarge
r6g.4xlarge
r5.4xlarge vs r6g.4xlarge: how to choose
r5.4xlarge pairs 16 vCPUs with 128GB of RAM at $1.0080/hr On-Demand (about $726/mo at 24×7). r6g.4xlarge pairs 16 vCPUs with 128GB at $0.8064/hr (~$581/mo). r6g.4xlarge is 20% cheaper per hour than r5.4xlarge ($0.2016/hr gap).
These are different generations of the same series. **r6g.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 r6g.4xlarge delivers ~226% more single-thread Sysbench score per dollar (1084 vs 3535 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 45612) are what to weigh. Spot pricing flips many of these comparisons — when r5.4xlarge drops to $0.2749/hr and r6g.4xlarge drops to $0.2476/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 r6g.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.
On-Demand Price Comparison
Monthly trajectory
Spot Price Comparison
30-Day daily trajectory