AWS trn1.2xlargevsAWS trn1.32xlarge

trn1.2xlarge pairs 8 vCPUs with 32GB of RAM at $1.3438/hr On-Demand (about $968/mo at 24×7). trn1.32xlarge pairs 128 vCPUs with 512GB at $21.5000/hr (~$15480/mo). trn1.2xlarge is 1500% cheaper per hour than trn1.32xlarge ($20.1563/hr gap).

Because both instances are in the **trn1 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: trn1.2xlarge gives you 8 vCPUs and 32GB of RAM, trn1.32xlarge gives you 128 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 2981/12530 for trn1.2xlarge and pending for trn1.32xlarge. 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 trn1.2xlarge when your workload is closer to Trainium ML training (ML training on AWS Trainium as a cheaper alternative to NVIDIA). Pick trn1.32xlarge when it's closer to Trainium ML training (ML training on AWS Trainium as a cheaper alternative to NVIDIA). 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.