AWS h1.16xlargevsAWS h1.4xlarge

h1.16xlarge pairs 64 vCPUs with 256GB of RAM at $3.7440/hr On-Demand (about $2696/mo at 24×7). h1.4xlarge pairs 16 vCPUs with 64GB at $0.9360/hr (~$674/mo). h1.4xlarge is 75% cheaper per hour than h1.16xlarge ($2.8080/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, h1.4xlarge gives you 16 vCPUs and 64GB. 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 2965/24873 for h1.4xlarge. 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 h1.16xlarge when your workload is closer to storage-optimized (general-purpose workloads). Pick h1.4xlarge 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.