AWS m5d.2xlargevsAWS m5d.4xlarge

m5d.2xlarge pairs 8 vCPUs with 32GB of RAM at $0.4520/hr On-Demand (about $325/mo at 24×7). m5d.4xlarge pairs 16 vCPUs with 64GB at $0.9040/hr (~$651/mo). m5d.2xlarge is 100% cheaper per hour than m5d.4xlarge ($0.4520/hr gap).

Because both instances are in the **m5d 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: m5d.2xlarge gives you 8 vCPUs and 32GB of RAM, m5d.4xlarge gives you 16 vCPUs and 64GB. 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 m5d.2xlarge delivers ~100% more single-thread Sysbench score per dollar (2341 vs 1171 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 (6453 vs 13029) are what to weigh. Spot pricing flips many of these comparisons — when m5d.2xlarge drops to $0.2888/hr and m5d.4xlarge drops to $0.3697/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick m5d.2xlarge when your workload is closer to general-purpose (balanced general-purpose workloads with a 1:4 vCPU-to-memory ratio). Pick m5d.4xlarge 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.