AWS m8idb.4xlargevsAWS m8idb.large

m8idb.4xlarge pairs 16 vCPUs with 64GB of RAM at $1.5275/hr On-Demand (about $1100/mo at 24×7). m8idb.large pairs 2 vCPUs with 8GB at $0.1909/hr (~$137/mo). m8idb.large is 88% cheaper per hour than m8idb.4xlarge ($1.3366/hr gap).

Because both instances are in the **m8idb 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: m8idb.4xlarge gives you 16 vCPUs and 64GB of RAM, m8idb.large gives you 2 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 m8idb.large delivers ~694% more single-thread Sysbench score per dollar (2197 vs 17451 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 (28271 vs 3532) are what to weigh. Spot pricing flips many of these comparisons — when m8idb.4xlarge drops to $0.6790/hr and m8idb.large drops to $0.0506/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick m8idb.4xlarge when your workload is closer to general-purpose (balanced general-purpose workloads with a 1:4 vCPU-to-memory ratio). Pick m8idb.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.