AWS m5a.2xlargevsAWS m5a.large

m5a.2xlarge pairs 8 vCPUs with 32GB of RAM at $0.3440/hr On-Demand (about $248/mo at 24×7). m5a.large pairs 2 vCPUs with 8GB at $0.0860/hr (~$62/mo). m5a.large is 75% cheaper per hour than m5a.2xlarge ($0.2580/hr gap).

Because both instances are in the **m5a family**, the only thing that changes between them is sizing — same silicon, same architecture (AMD EPYC (x86_64)), same burstable/sustained behavior. The choice is purely about how much capacity you actually need: m5a.2xlarge gives you 8 vCPUs and 32GB of RAM, m5a.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 m5a.large delivers ~297% more single-thread Sysbench score per dollar (3683 vs 14616 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 (5251 vs 1296) are what to weigh. Spot pricing flips many of these comparisons — when m5a.2xlarge drops to $0.1254/hr and m5a.large drops to $0.0385/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick m5a.2xlarge when your workload is closer to general-purpose (balanced general-purpose workloads with a 1:4 vCPU-to-memory ratio). Pick m5a.large when it's closer to general-purpose (balanced general-purpose workloads with a 1:4 vCPU-to-memory ratio). 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.