AWS m7gd.16xlargevsAWS m7gd.4xlarge

m7gd.16xlarge pairs 64 vCPUs with 256GB of RAM at $3.4171/hr On-Demand (about $2460/mo at 24×7). m7gd.4xlarge pairs 16 vCPUs with 64GB at $0.8543/hr (~$615/mo). m7gd.4xlarge is 75% cheaper per hour than m7gd.16xlarge ($2.5628/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.16xlarge gives you 64 vCPUs and 256GB of RAM, m7gd.4xlarge gives you 16 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.

Benchmark data for at least one of these instances is still being collected, so a direct performance-per-dollar comparison isn't possible yet. Sysbench scores are pending for m7gd.16xlarge and 3018/48039 for m7gd.4xlarge. Check back as the benchmark queue completes — newer-generation instances typically score 10–30% higher on single-thread and 15–50% higher on multi-core vs the previous generation in the same series.

In practice, pick m7gd.16xlarge when your workload is closer to general-purpose (balanced general-purpose workloads with a 1:4 vCPU-to-memory ratio). Pick m7gd.4xlarge 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.