AWS im4gn.2xlargevsAWS im4gn.large

im4gn.2xlarge pairs 8 vCPUs with 32GB of RAM at $0.7276/hr On-Demand (about $524/mo at 24×7). im4gn.large pairs 2 vCPUs with 8GB at $0.1819/hr (~$131/mo). im4gn.large is 75% cheaper per hour than im4gn.2xlarge ($0.5457/hr gap).

Because both instances are in the **im4gn family**, the only thing that changes between them is sizing — same silicon, same architecture (arm64), same burstable/sustained behavior. The choice is purely about how much capacity you actually need: im4gn.2xlarge gives you 8 vCPUs and 32GB of RAM, im4gn.large gives you 2 vCPUs and 8GB. 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 im4gn.large delivers ~300% more single-thread Sysbench score per dollar (3857 vs 15426 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 (22189 vs 5327) are what to weigh. Spot pricing flips many of these comparisons — when im4gn.2xlarge drops to $0.1698/hr and im4gn.large drops to $0.0579/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick im4gn.2xlarge when your workload is closer to general-purpose (general-purpose workloads). Pick im4gn.large when it's closer to general-purpose (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.