AWS r7a.4xlargevsAWS r7a.metal-48xl

r7a.4xlarge pairs 16 vCPUs with 128GB of RAM at $1.2172/hr On-Demand (about $876/mo at 24×7). r7a.metal-48xl pairs 192 vCPUs with 1536GB at $14.6064/hr (~$10517/mo). r7a.4xlarge is 1100% cheaper per hour than r7a.metal-48xl ($13.3892/hr gap).

Because both instances are in the **r7a 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: r7a.4xlarge gives you 16 vCPUs and 128GB of RAM, r7a.metal-48xl 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 4539/72304 for r7a.4xlarge and pending for r7a.metal-48xl. 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 r7a.4xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r7a.metal-48xl 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.