AWS c6g.metalvsAWS c6g.xlarge

c6g.metal pairs 64 vCPUs with 128GB of RAM at $2.1760/hr On-Demand (about $1567/mo at 24×7). c6g.xlarge pairs 4 vCPUs with 8GB at $0.1360/hr (~$98/mo). c6g.xlarge is 94% cheaper per hour than c6g.metal ($2.0400/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.metal gives you 64 vCPUs and 128GB of RAM, c6g.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 c6g.xlarge delivers ~1496% more single-thread Sysbench score per dollar (1292 vs 20625 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 (179406 vs 10958) are what to weigh. Spot pricing flips many of these comparisons — when c6g.metal drops to $0.6400/hr and c6g.xlarge drops to $0.0575/hr, the cheap-per-hour winner can swing meaningfully.

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