AWS r6a.24xlargevsAWS r6a.metal

r6a.24xlarge pairs 96 vCPUs with 768GB of RAM at $5.4432/hr On-Demand (about $3919/mo at 24×7). r6a.metal pairs 192 vCPUs with 1536GB at $10.8864/hr (~$7838/mo). r6a.24xlarge is 100% cheaper per hour than r6a.metal ($5.4432/hr gap).

Because both instances are in the **r6a family**, the only thing that changes between them is sizing — same silicon, same architecture (AMD EPYC (x86_64)), same burstable/sustained behavior. The choice is purely about how much capacity you actually need: r6a.24xlarge gives you 96 vCPUs and 768GB of RAM, r6a.metal gives you 192 vCPUs and 1536GB. 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.

Benchmark data for at least one of these instances is still being collected, so a direct performance-per-dollar comparison isn't possible yet. Sysbench scores are 4078/217304 for r6a.24xlarge and pending for r6a.metal. Check back as the benchmark queue completes — newer-generation instances typically score 10–30% higher on single-thread and 15–50% higher on multi-core vs the previous generation in the same series.

In practice, pick r6a.24xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r6a.metal when it's closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). 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.