AWS m7gd.metalvsAWS m7gd.xlarge

m7gd.metal pairs 64 vCPUs with 256GB of RAM at $3.4171/hr On-Demand (about $2460/mo at 24×7). m7gd.xlarge pairs 4 vCPUs with 16GB at $0.2136/hr (~$154/mo). m7gd.xlarge is 94% cheaper per hour than m7gd.metal ($3.2035/hr gap).

Because both instances are in the **m7gd 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: m7gd.metal gives you 64 vCPUs and 256GB of RAM, m7gd.xlarge gives you 4 vCPUs and 16GB. 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 m7gd.xlarge delivers ~1496% more single-thread Sysbench score per dollar (884 vs 14110 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 (192810 vs 11815) are what to weigh. Spot pricing flips many of these comparisons — when m7gd.metal drops to $0.6044/hr and m7gd.xlarge drops to $0.1157/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick m7gd.metal when your workload is closer to general-purpose (balanced general-purpose workloads with a 1:4 vCPU-to-memory ratio). Pick m7gd.xlarge when it's closer to general-purpose (balanced general-purpose workloads with a 1:4 vCPU-to-memory ratio). 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.