AWS i4g.16xlargevsAWS i4g.xlarge

i4g.16xlarge pairs 64 vCPUs with 512GB of RAM at $4.9421/hr On-Demand (about $3558/mo at 24×7). i4g.xlarge pairs 4 vCPUs with 32GB at $0.3089/hr (~$222/mo). i4g.xlarge is 94% cheaper per hour than i4g.16xlarge ($4.6332/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.16xlarge gives you 64 vCPUs and 512GB of RAM, i4g.xlarge gives you 4 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.

On raw price-per-performance, the two are i4g.xlarge delivers ~1502% more single-thread Sysbench score per dollar (568 vs 9101 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 (179035 vs 10930) are what to weigh. Spot pricing flips many of these comparisons — when i4g.16xlarge drops to $1.3637/hr and i4g.xlarge drops to $0.0836/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick i4g.16xlarge when your workload is closer to storage-optimized (NVMe SSD) (I/O-bound work needing low-latency NVMe local storage — NoSQL, search). Pick i4g.xlarge 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.