AWS m7g.largevsAWS m7gd.large

m7g.large pairs 2 vCPUs with 8GB of RAM at $0.0816/hr On-Demand (about $59/mo at 24×7). m7gd.large pairs 2 vCPUs with 8GB at $0.1068/hr (~$77/mo). m7g.large is 31% cheaper per hour than m7gd.large ($0.0252/hr gap).

Both are generation-7 general-purpose instances, but they run on different silicon: **m7g.large** is AWS Graviton (ARM64), **m7gd.large** 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 m7g.large delivers ~31% more single-thread Sysbench score per dollar (36924 vs 28230 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 (5811 vs 5807) are what to weigh. Spot pricing flips many of these comparisons — when m7g.large drops to $0.0400/hr and m7gd.large drops to $0.0504/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick m7g.large when your workload is closer to general-purpose (balanced general-purpose workloads with a 1:4 vCPU-to-memory ratio). Pick m7gd.large 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.