AWS m8gb.4xlargevsAWS m8gb.xlarge

m8gb.4xlarge pairs 16 vCPUs with 64GB of RAM at $1.1640/hr On-Demand (about $838/mo at 24×7). m8gb.xlarge pairs 4 vCPUs with 16GB at $0.2910/hr (~$210/mo). m8gb.xlarge is 75% cheaper per hour than m8gb.4xlarge ($0.8730/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.4xlarge gives you 16 vCPUs and 64GB of RAM, m8gb.xlarge gives you 4 vCPUs and 16GB. 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.xlarge delivers ~300% more single-thread Sysbench score per dollar (2866 vs 11457 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 (53169 vs 13191) are what to weigh. Spot pricing flips many of these comparisons — when m8gb.4xlarge drops to $0.3309/hr and m8gb.xlarge drops to $0.1114/hr, the cheap-per-hour winner can swing meaningfully.

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