AWS m1.mediumvsAWS m1.xlarge

m1.medium pairs 1 vCPUs with 3.8GB of RAM at $0.0870/hr On-Demand (about $63/mo at 24×7). m1.xlarge pairs 4 vCPUs with 15GB at $0.3500/hr (~$252/mo). m1.medium is 302% cheaper per hour than m1.xlarge ($0.2630/hr gap).

Because both instances are in the **m1 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: m1.medium gives you 1 vCPUs and 3.8GB of RAM, m1.xlarge gives you 4 vCPUs and 15GB. 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 m1.medium delivers ~284% more single-thread Sysbench score per dollar (8356 vs 2174 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 (732 vs 2468) are what to weigh. Spot pricing flips many of these comparisons — when m1.medium drops to $0.0182/hr and m1.xlarge drops to $0.1034/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick m1.medium when your workload is closer to general-purpose (balanced general-purpose workloads with a 1:4 vCPU-to-memory ratio). Pick m1.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.