AWS z1d.12xlargevsAWS z1d.metal

z1d.12xlarge pairs 48 vCPUs with 384GB of RAM at $4.4640/hr On-Demand (about $3214/mo at 24×7). z1d.metal pairs 48 vCPUs with 384GB at $4.4640/hr (~$3214/mo). Both are priced identically per hour on-demand.

z1d.12xlarge (high-frequency compute, Intel Xeon (x86_64)) and z1d.metal (high-frequency compute, Intel Xeon (x86_64)) target different workload shapes. The vCPU:RAM ratios are different (48:384 vs 48:384), and depending on the architectures involved you may also see meaningful single-thread performance and per-hour-cost differences. This kind of cross-category comparison is most useful when you're early in the design phase and not yet sure whether your workload is CPU-bound, memory-bound, or balanced — once that's clear, the right pick is usually obvious.

Benchmark data for at least one of these instances is still being collected, so a direct performance-per-dollar comparison isn't possible yet. Sysbench scores are 1368/50684 for z1d.12xlarge and pending for z1d.metal. Check back as the benchmark queue completes — newer-generation instances typically score 10–30% higher on single-thread and 15–50% higher on multi-core vs the previous generation in the same series.

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.metal 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.