AWS t3.2xlargevsAWS t3.large

t3.2xlarge pairs 8 vCPUs with 32GB of RAM at $0.3328/hr On-Demand (about $240/mo at 24×7). t3.large pairs 2 vCPUs with 8GB at $0.0832/hr (~$60/mo). t3.large is 75% cheaper per hour than t3.2xlarge ($0.2496/hr gap).

Because both instances are in the **t3 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: t3.2xlarge gives you 8 vCPUs and 32GB of RAM, t3.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 t3.large delivers ~309% more single-thread Sysbench score per dollar (3179 vs 13017 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 (6523 vs 1590) are what to weigh. Spot pricing flips many of these comparisons — when t3.2xlarge drops to $0.0958/hr and t3.large drops to $0.0363/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick t3.2xlarge when your workload is closer to burstable general-purpose (bursty traffic — web apps, dev/test boxes, CI runners, small databases). Pick t3.large 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.