AWS m6g.4xlargevsAWS m6g.8xlarge

m6g.4xlarge pairs 16 vCPUs with 64GB of RAM at $0.6160/hr On-Demand (about $444/mo at 24×7). m6g.8xlarge pairs 32 vCPUs with 128GB at $1.2320/hr (~$887/mo). m6g.4xlarge is 100% cheaper per hour than m6g.8xlarge ($0.6160/hr gap).

Because both instances are in the **m6g 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: m6g.4xlarge gives you 16 vCPUs and 64GB of RAM, m6g.8xlarge gives you 32 vCPUs and 128GB. 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 m6g.4xlarge delivers ~100% more single-thread Sysbench score per dollar (4554 vs 2278 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 (44630 vs 89502) are what to weigh. Spot pricing flips many of these comparisons — when m6g.4xlarge drops to $0.2325/hr and m6g.8xlarge drops to $0.3971/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick m6g.4xlarge when your workload is closer to general-purpose (balanced general-purpose workloads with a 1:4 vCPU-to-memory ratio). Pick m6g.8xlarge 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.