AWS c8i-flex.12xlargevsAWS c8i-flex.8xlarge

c8i-flex.12xlarge pairs 48 vCPUs with 96GB of RAM at $2.1365/hr On-Demand (about $1538/mo at 24×7). c8i-flex.8xlarge pairs 32 vCPUs with 64GB at $1.4243/hr (~$1026/mo). c8i-flex.8xlarge is 33% cheaper per hour than c8i-flex.12xlarge ($0.7122/hr gap).

Because both instances are in the **c8i 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: c8i-flex.12xlarge gives you 48 vCPUs and 96GB of RAM, c8i-flex.8xlarge gives you 32 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 c8i-flex.8xlarge delivers ~51% more single-thread Sysbench score per dollar (1555 vs 2342 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 (84021 vs 56368) are what to weigh. Spot pricing flips many of these comparisons — when c8i-flex.12xlarge drops to $0.6794/hr and c8i-flex.8xlarge drops to $0.6863/hr, the cheap-per-hour winner can swing meaningfully.

In practice, pick c8i-flex.12xlarge when your workload is closer to compute-optimized (CPU-bound work — batch processing, web servers under sustained load, game servers). Pick c8i-flex.8xlarge when it's closer to compute-optimized (CPU-bound work — batch processing, web servers under sustained load, game servers). 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.