AWS c7a.8xlargevsAWS c7g.8xlarge

c7a.8xlarge pairs 32 vCPUs with 64GB of RAM at $1.6422/hr On-Demand (about $1182/mo at 24×7). c7g.8xlarge pairs 32 vCPUs with 64GB at $1.1600/hr (~$835/mo). c7g.8xlarge is 29% cheaper per hour than c7a.8xlarge ($0.4822/hr gap).

Both are generation-7 compute-optimized instances, but they run on different silicon: **c7a.8xlarge** is AMD EPYC (x86_64), **c7g.8xlarge** is AWS Graviton (ARM64). 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 roughly tied on single-thread performance per dollar (2562 vs 2601 Sysbench 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 (133944 vs 96227) are what to weigh. Spot pricing flips many of these comparisons — when c7a.8xlarge drops to $0.6043/hr and c7g.8xlarge drops to $0.3556/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick c7a.8xlarge when your workload is closer to compute-optimized (CPU-bound work — batch processing, web servers under sustained load, game servers). Pick c7g.8xlarge 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.