AWS c5d.4xlargevsAWS c5d.large

c5d.4xlarge pairs 16 vCPUs with 32GB of RAM at $0.7680/hr On-Demand (about $553/mo at 24×7). c5d.large pairs 2 vCPUs with 4GB at $0.0960/hr (~$69/mo). c5d.large is 87% cheaper per hour than c5d.4xlarge ($0.6720/hr gap).

Because both instances are in the **c5d 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: c5d.4xlarge gives you 16 vCPUs and 32GB of RAM, c5d.large gives you 2 vCPUs and 4GB. 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 c5d.large delivers ~754% more single-thread Sysbench score per dollar (1512 vs 12917 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 (14282 vs 1860) are what to weigh. Spot pricing flips many of these comparisons — when c5d.4xlarge drops to $0.3311/hr and c5d.large drops to $0.0349/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick c5d.4xlarge when your workload is closer to compute-optimized (CPU-bound work — batch processing, web servers under sustained load, game servers). Pick c5d.large when it's closer to compute-optimized (CPU-bound work — batch processing, web servers under sustained load, game servers). 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.