AWS c8gn.16xlargevsAWS c8gn.4xlarge

c8gn.16xlarge pairs 64 vCPUs with 128GB of RAM at $3.7920/hr On-Demand (about $2730/mo at 24×7). c8gn.4xlarge pairs 16 vCPUs with 32GB at $0.9480/hr (~$683/mo). c8gn.4xlarge is 75% cheaper per hour than c8gn.16xlarge ($2.8440/hr gap).

Because both instances are in the **c8gn family**, the only thing that changes between them is sizing — same silicon, same architecture (AWS Graviton (ARM64)), same burstable/sustained behavior. The choice is purely about how much capacity you actually need: c8gn.16xlarge gives you 64 vCPUs and 128GB of RAM, c8gn.4xlarge gives you 16 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 c8gn.4xlarge delivers ~302% more single-thread Sysbench score per dollar (878 vs 3527 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 (213037 vs 53513) are what to weigh. Spot pricing flips many of these comparisons — when c8gn.16xlarge drops to $0.9996/hr and c8gn.4xlarge drops to $0.2711/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick c8gn.16xlarge when your workload is closer to compute-optimized (CPU-bound work — batch processing, web servers under sustained load, game servers). Pick c8gn.4xlarge 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.