AWS r6g.4xlargevsAWS r6g.metal

r6g.4xlarge pairs 16 vCPUs with 128GB of RAM at $0.8064/hr On-Demand (about $581/mo at 24×7). r6g.metal pairs 64 vCPUs with 512GB at $3.2256/hr (~$2322/mo). r6g.4xlarge is 300% cheaper per hour than r6g.metal ($2.4192/hr gap).

Because both instances are in the **r6g 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: r6g.4xlarge gives you 16 vCPUs and 128GB of RAM, r6g.metal gives you 64 vCPUs and 512GB. 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 2851/45612 for r6g.4xlarge and pending for r6g.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 r6g.4xlarge when your workload is closer to memory-optimized (memory-bound work — in-memory databases, real-time analytics, large caches). Pick r6g.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.