AWS i8ge.6xlargevsAWS i8ge.large

i8ge.6xlarge pairs 24 vCPUs with 192GB of RAM at $2.8476/hr On-Demand (about $2050/mo at 24×7). i8ge.large pairs 2 vCPUs with 16GB at $0.2373/hr (~$171/mo). i8ge.large is 92% cheaper per hour than i8ge.6xlarge ($2.6103/hr gap).

Because both instances are in the **i8ge 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: i8ge.6xlarge gives you 24 vCPUs and 192GB of RAM, i8ge.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 i8ge.large delivers ~1099% more single-thread Sysbench score per dollar (1172 vs 14050 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 (79829 vs 6510) are what to weigh. Spot pricing flips many of these comparisons — when i8ge.6xlarge drops to $0.6128/hr and i8ge.large drops to $0.0563/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick i8ge.6xlarge when your workload is closer to storage-optimized (NVMe SSD) (I/O-bound work needing low-latency NVMe local storage — NoSQL, search). Pick i8ge.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.