AWS c3.2xlargevsAWS c3.large

c3.2xlarge pairs 8 vCPUs with 15GB of RAM at $0.4200/hr On-Demand (about $302/mo at 24×7). c3.large pairs 2 vCPUs with 3.8GB at $0.1050/hr (~$76/mo). c3.large is 75% cheaper per hour than c3.2xlarge ($0.3150/hr gap).

Because both instances are in the **c3 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: c3.2xlarge gives you 8 vCPUs and 15GB of RAM, c3.large gives you 2 vCPUs and 3.8GB. 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 c3.large delivers ~294% more single-thread Sysbench score per dollar (2540 vs 10010 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 (6517 vs 1576) are what to weigh. Spot pricing flips many of these comparisons — when c3.2xlarge drops to $0.1708/hr and c3.large drops to $0.0356/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick c3.2xlarge when your workload is closer to compute-optimized (CPU-bound work — batch processing, web servers under sustained load, game servers). Pick c3.large when it's closer to compute-optimized (CPU-bound work — batch processing, web servers under sustained load, game servers). 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.