AWS r6id.16xlargevsAWS r6id.4xlarge

r6id.16xlarge pairs 64 vCPUs with 512GB of RAM at $4.8384/hr On-Demand (about $3484/mo at 24×7). r6id.4xlarge pairs 16 vCPUs with 128GB at $1.2096/hr (~$871/mo). r6id.4xlarge is 75% cheaper per hour than r6id.16xlarge ($3.6288/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.16xlarge gives you 64 vCPUs and 512GB of RAM, r6id.4xlarge gives you 16 vCPUs and 128GB. 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.

Benchmark data for at least one of these instances is still being collected, so a direct performance-per-dollar comparison isn't possible yet. Sysbench scores are pending for r6id.16xlarge and 2979/24782 for r6id.4xlarge. Check back as the benchmark queue completes — newer-generation instances typically score 10–30% higher on single-thread and 15–50% higher on multi-core vs the previous generation in the same series.

In practice, pick r6id.16xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r6id.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.