AWS r8idb.4xlargevsAWS r8idb.large

r8idb.4xlarge pairs 16 vCPUs with 128GB of RAM at $1.8758/hr On-Demand (about $1351/mo at 24×7). r8idb.large pairs 2 vCPUs with 16GB at $0.2345/hr (~$169/mo). r8idb.large is 87% cheaper per hour than r8idb.4xlarge ($1.6413/hr gap).

Because both instances are in the **r8idb 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: r8idb.4xlarge gives you 16 vCPUs and 128GB of RAM, r8idb.large gives you 2 vCPUs and 16GB. 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 r8idb.large delivers ~693% more single-thread Sysbench score per dollar (1791 vs 14207 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 (28236 vs 3536) are what to weigh. Spot pricing flips many of these comparisons — when r8idb.4xlarge drops to $0.9428/hr and r8idb.large drops to $0.0675/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick r8idb.4xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r8idb.large 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.