AWS t3.largevsAWS t3.nano

t3.large pairs 2 vCPUs with 8GB of RAM at $0.0832/hr On-Demand (about $60/mo at 24×7). t3.nano pairs 2 vCPUs with 0.5GB at $0.0052/hr (~$4/mo). t3.nano is 94% cheaper per hour than t3.large ($0.0780/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.large gives you 2 vCPUs and 8GB of RAM, t3.nano gives you 2 vCPUs and 0.5GB. 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.nano delivers ~1472% more single-thread Sysbench score per dollar (13017 vs 204615 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 (1590 vs 1656) are what to weigh. Spot pricing flips many of these comparisons — when t3.large drops to $0.0363/hr and t3.nano drops to $0.0015/hr, the cheap-per-hour winner can swing meaningfully.

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