AWS t2.xlargevsAWS t3a.xlarge

t2.xlarge pairs 4 vCPUs with 16GB of RAM at $0.1856/hr On-Demand (about $134/mo at 24×7). t3a.xlarge pairs 4 vCPUs with 16GB at $0.1504/hr (~$108/mo). t3a.xlarge is 19% cheaper per hour than t2.xlarge ($0.0352/hr gap).

These are different generations of the same series. **t3a.xlarge** is the newer generation, and AWS's pattern across generations is fairly consistent: ~10–15% better single-thread, 15–30% better multi-core, and similar or modestly higher per-hour pricing — so the price/performance per dollar usually improves with each generation. **t2.xlarge** is still available and still works (AWS doesn't retire instance types quickly), but for new workloads the newer generation is typically the better default unless you have a specific reason to pin to the older AMI or there's a meaningful regional pricing advantage today.

On raw price-per-performance, the two are t3a.xlarge delivers ~65% more single-thread Sysbench score per dollar (4892 vs 8078 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 (3540 vs 2618) are what to weigh. Spot pricing flips many of these comparisons — when t2.xlarge drops to $0.0550/hr and t3a.xlarge drops to $0.0583/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick t2.xlarge when your workload is closer to burstable general-purpose (bursty traffic — web apps, dev/test boxes, CI runners, small databases). Pick t3a.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.