AWS c6g.4xlargevsAWS c6g.8xlarge

c6g.4xlarge pairs 16 vCPUs with 32GB of RAM at $0.5440/hr On-Demand (about $392/mo at 24×7). c6g.8xlarge pairs 32 vCPUs with 64GB at $1.0880/hr (~$783/mo). c6g.4xlarge is 100% cheaper per hour than c6g.8xlarge ($0.5440/hr gap).

Because both instances are in the **c6g 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: c6g.4xlarge gives you 16 vCPUs and 32GB of RAM, c6g.8xlarge gives you 32 vCPUs and 64GB. 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 c6g.4xlarge delivers ~100% more single-thread Sysbench score per dollar (5158 vs 2580 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 (44644 vs 89504) are what to weigh. Spot pricing flips many of these comparisons — when c6g.4xlarge drops to $0.1723/hr and c6g.8xlarge drops to $0.3506/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick c6g.4xlarge when your workload is closer to compute-optimized (CPU-bound work — batch processing, web servers under sustained load, game servers). Pick c6g.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.