AWS z1d.3xlargevsAWS z1d.large

z1d.3xlarge pairs 12 vCPUs with 96GB of RAM at $1.1160/hr On-Demand (about $804/mo at 24×7). z1d.large pairs 2 vCPUs with 16GB at $0.1860/hr (~$134/mo). z1d.large is 83% cheaper per hour than z1d.3xlarge ($0.9300/hr gap).

Because both instances are in the **z1d 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: z1d.3xlarge gives you 12 vCPUs and 96GB of RAM, z1d.large gives you 2 vCPUs and 16GB. 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 z1d.large delivers ~489% more single-thread Sysbench score per dollar (1225 vs 7210 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 (12611 vs 2011) are what to weigh. Spot pricing flips many of these comparisons — when z1d.3xlarge drops to $0.3201/hr and z1d.large drops to $0.0507/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick z1d.3xlarge when your workload is closer to high-frequency compute (workloads needing the highest single-thread clock — EDA, certain RDBMS). Pick z1d.large when it's closer to high-frequency compute (workloads needing the highest single-thread clock — EDA, certain RDBMS). 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.