AWS z1d.12xlargevsAWS z1d.xlarge

z1d.12xlarge pairs 48 vCPUs with 384GB of RAM at $4.4640/hr On-Demand (about $3214/mo at 24×7). z1d.xlarge pairs 4 vCPUs with 32GB at $0.3720/hr (~$268/mo). z1d.xlarge is 92% cheaper per hour than z1d.12xlarge ($4.0920/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.12xlarge gives you 48 vCPUs and 384GB of RAM, z1d.xlarge gives you 4 vCPUs and 32GB. 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.xlarge delivers ~1100% more single-thread Sysbench score per dollar (306 vs 3672 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 (50684 vs 4139) are what to weigh. Spot pricing flips many of these comparisons — when z1d.12xlarge drops to $2.0510/hr and z1d.xlarge drops to $0.1153/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick z1d.12xlarge when your workload is closer to high-frequency compute (workloads needing the highest single-thread clock — EDA, certain RDBMS). Pick z1d.xlarge 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.