AWS c6gd.8xlargevsAWS c6gd.xlarge

c6gd.8xlarge pairs 32 vCPUs with 64GB of RAM at $1.2288/hr On-Demand (about $885/mo at 24×7). c6gd.xlarge pairs 4 vCPUs with 8GB at $0.1536/hr (~$111/mo). c6gd.xlarge is 87% cheaper per hour than c6gd.8xlarge ($1.0752/hr gap).

Because both instances are in the **c6gd 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: c6gd.8xlarge gives you 32 vCPUs and 64GB of RAM, c6gd.xlarge gives you 4 vCPUs and 8GB. 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 c6gd.xlarge delivers ~700% more single-thread Sysbench score per dollar (2283 vs 18268 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 (89488 vs 10965) are what to weigh. Spot pricing flips many of these comparisons — when c6gd.8xlarge drops to $0.3524/hr and c6gd.xlarge drops to $0.0525/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick c6gd.8xlarge when your workload is closer to compute-optimized (CPU-bound work — batch processing, web servers under sustained load, game servers). Pick c6gd.xlarge 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.