AWS m8id.4xlargevsAWS m8id.96xlarge

m8id.4xlarge pairs 16 vCPUs with 64GB of RAM at $1.0442/hr On-Demand (about $752/mo at 24×7). m8id.96xlarge pairs 384 vCPUs with 1536GB at $25.0598/hr (~$18043/mo). m8id.4xlarge is 2300% cheaper per hour than m8id.96xlarge ($24.0157/hr gap).

Because both instances are in the **m8id family**, the only thing that changes between them is sizing — same silicon, same architecture (Intel Xeon (x86_64)), same burstable/sustained behavior. The choice is purely about how much capacity you actually need: m8id.4xlarge gives you 16 vCPUs and 64GB of RAM, m8id.96xlarge gives you 384 vCPUs and 1536GB. 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 3348/28123 for m8id.4xlarge and pending for m8id.96xlarge. 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 m8id.4xlarge when your workload is closer to general-purpose (balanced general-purpose workloads with a 1:4 vCPU-to-memory ratio). Pick m8id.96xlarge 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.