AWS i3.2xlargevsAWS i3.4xlarge

i3.2xlarge pairs 8 vCPUs with 61GB of RAM at $0.6240/hr On-Demand (about $449/mo at 24×7). i3.4xlarge pairs 16 vCPUs with 122GB at $1.2480/hr (~$899/mo). i3.2xlarge is 100% cheaper per hour than i3.4xlarge ($0.6240/hr gap).

Because both instances are in the **i3 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: i3.2xlarge gives you 8 vCPUs and 61GB of RAM, i3.4xlarge gives you 16 vCPUs and 122GB. 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 i3.2xlarge delivers ~99% more single-thread Sysbench score per dollar (1449 vs 728 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 (5337 vs 10771) are what to weigh. Spot pricing flips many of these comparisons — when i3.2xlarge drops to $0.3911/hr and i3.4xlarge drops to $0.5908/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick i3.2xlarge when your workload is closer to storage-optimized (NVMe SSD) (I/O-bound work needing low-latency NVMe local storage — NoSQL, search). Pick i3.4xlarge when it's closer to storage-optimized (NVMe SSD) (I/O-bound work needing low-latency NVMe local storage — NoSQL, search). 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.