AWS r6id.2xlargevsAWS r6id.8xlarge

r6id.2xlarge pairs 8 vCPUs with 64GB of RAM at $0.6048/hr On-Demand (about $435/mo at 24×7). r6id.8xlarge pairs 32 vCPUs with 256GB at $2.4192/hr (~$1742/mo). r6id.2xlarge is 300% cheaper per hour than r6id.8xlarge ($1.8144/hr gap).

Because both instances are in the **r6id 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: r6id.2xlarge gives you 8 vCPUs and 64GB of RAM, r6id.8xlarge gives you 32 vCPUs and 256GB. 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 r6id.2xlarge delivers ~303% more single-thread Sysbench score per dollar (4927 vs 1222 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 (12370 vs 49572) are what to weigh. Spot pricing flips many of these comparisons — when r6id.2xlarge drops to $0.2016/hr and r6id.8xlarge drops to $0.9883/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick r6id.2xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r6id.8xlarge 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.