AWS i4g.2xlargevsAWS i4g.large

i4g.2xlarge pairs 8 vCPUs with 64GB of RAM at $0.6178/hr On-Demand (about $445/mo at 24×7). i4g.large pairs 2 vCPUs with 16GB at $0.1544/hr (~$111/mo). i4g.large is 75% cheaper per hour than i4g.2xlarge ($0.4633/hr gap).

Because both instances are in the **i4g family**, the only thing that changes between them is sizing — same silicon, same architecture (AWS Graviton (ARM64)), same burstable/sustained behavior. The choice is purely about how much capacity you actually need: i4g.2xlarge gives you 8 vCPUs and 64GB of RAM, i4g.large gives you 2 vCPUs and 16GB. 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 i4g.large delivers ~300% more single-thread Sysbench score per dollar (4549 vs 18175 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 (22133 vs 5305) are what to weigh. Spot pricing flips many of these comparisons — when i4g.2xlarge drops to $0.1695/hr and i4g.large drops to $0.0411/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick i4g.2xlarge when your workload is closer to storage-optimized (NVMe SSD) (I/O-bound work needing low-latency NVMe local storage — NoSQL, search). Pick i4g.large 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.