AWS h1.16xlargevsAWS h1.2xlarge

h1.16xlarge pairs 64 vCPUs with 256GB of RAM at $3.7440/hr On-Demand (about $2696/mo at 24×7). h1.2xlarge pairs 8 vCPUs with 32GB at $0.4680/hr (~$337/mo). h1.2xlarge is 87% cheaper per hour than h1.16xlarge ($3.2760/hr gap).

Because both instances are in the **h1 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: h1.16xlarge gives you 64 vCPUs and 256GB of RAM, h1.2xlarge gives you 8 vCPUs and 32GB. 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 h1.16xlarge and 2337/11427 for h1.2xlarge. 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 h1.16xlarge when your workload is closer to storage-optimized (general-purpose workloads). Pick h1.2xlarge when it's closer to storage-optimized (general-purpose workloads). 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.