AWS t2.largevsAWS t2.xlarge

t2.large pairs 2 vCPUs with 8GB of RAM at $0.0928/hr On-Demand (about $67/mo at 24×7). t2.xlarge pairs 4 vCPUs with 16GB at $0.1856/hr (~$134/mo). t2.large is 100% cheaper per hour than t2.xlarge ($0.0928/hr gap).

Because both instances are in the **t2 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: t2.large gives you 2 vCPUs and 8GB of RAM, t2.xlarge gives you 4 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 t2.large delivers ~404% more single-thread Sysbench score per dollar (24634 vs 4892 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 (4221 vs 3540) are what to weigh. Spot pricing flips many of these comparisons — when t2.large drops to $0.0302/hr and t2.xlarge drops to $0.0555/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick t2.large when your workload is closer to burstable general-purpose (bursty traffic — web apps, dev/test boxes, CI runners, small databases). Pick t2.xlarge when it's closer to burstable general-purpose (bursty traffic — web apps, dev/test boxes, CI runners, small databases). 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.