AWS m6idn.8xlargevsAWS m6idn.large

m6idn.8xlarge pairs 32 vCPUs with 128GB of RAM at $2.5459/hr On-Demand (about $1833/mo at 24×7). m6idn.large pairs 2 vCPUs with 8GB at $0.1591/hr (~$115/mo). m6idn.large is 94% cheaper per hour than m6idn.8xlarge ($2.3868/hr gap).

Because both instances are in the **m6idn 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: m6idn.8xlarge gives you 32 vCPUs and 128GB of RAM, m6idn.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 m6idn.large delivers ~1491% more single-thread Sysbench score per dollar (1170 vs 18615 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 (49592 vs 3062) are what to weigh. Spot pricing flips many of these comparisons — when m6idn.8xlarge drops to $1.1308/hr and m6idn.large drops to $0.0468/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick m6idn.8xlarge when your workload is closer to general-purpose (balanced general-purpose workloads with a 1:4 vCPU-to-memory ratio). Pick m6idn.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.