AWS m8gb.2xlargevsAWS m8gb.4xlarge

m8gb.2xlarge pairs 8 vCPUs with 32GB of RAM at $0.5820/hr On-Demand (about $419/mo at 24×7). m8gb.4xlarge pairs 16 vCPUs with 64GB at $1.1640/hr (~$838/mo). m8gb.2xlarge is 100% cheaper per hour than m8gb.4xlarge ($0.5820/hr gap).

Because both instances are in the **m8gb 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: m8gb.2xlarge gives you 8 vCPUs and 32GB of RAM, m8gb.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.

On raw price-per-performance, the two are m8gb.2xlarge delivers ~100% more single-thread Sysbench score per dollar (5730 vs 2866 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 (26526 vs 53169) are what to weigh. Spot pricing flips many of these comparisons — when m8gb.2xlarge drops to $0.2331/hr and m8gb.4xlarge drops to $0.3309/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick m8gb.2xlarge when your workload is closer to general-purpose (balanced general-purpose workloads with a 1:4 vCPU-to-memory ratio). Pick m8gb.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.