AWS c8a.largevsAWS c8id.large

c8a.large pairs 2 vCPUs with 4GB of RAM at $0.1078/hr On-Demand (about $78/mo at 24×7). c8id.large pairs 2 vCPUs with 4GB at $0.1109/hr (~$80/mo). c8a.large is 3% cheaper per hour than c8id.large ($0.0031/hr gap).

Both are generation-8 compute-optimized instances, but they run on different silicon: **c8a.large** is AMD EPYC (x86_64), **c8id.large** is Intel Xeon (x86_64). AMD variants (suffix `a`) are typically 10% cheaper than Intel siblings at comparable single-thread performance. Graviton variants (suffix `g`) are usually 20–40% cheaper but require ARM64-compatible binaries — most modern Linux stacks are fine, but verify any compiled extensions, native modules, or third-party binaries before migrating. Same vCPU/RAM ratio, same network performance class, different processor.

On raw price-per-performance, the two are c8a.large delivers ~71% more single-thread Sysbench score per dollar (51489 vs 30041 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 (10896 vs 3534) are what to weigh. Spot pricing flips many of these comparisons — when c8a.large drops to $0.0339/hr and c8id.large drops to $0.0371/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick c8a.large when your workload is closer to compute-optimized (CPU-bound work — batch processing, web servers under sustained load, game servers). Pick c8id.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.