Running AI Inference Using EC2 GPUs: An Intro and Comparison to CPUs

This post explains how to run AI inference for transformer models on AWS EC2 GPU instances (such as p3 and g4dn) using a PyTorch-based workflow: selecting an instance and AMI, activating the environment, loading a pretrained GPT-2 model, moving it to GPU, and running a simple text-generation example. It also summarizes trade-offs between a self-managed EC2 approach and the managed Amazon SageMaker service in terms of control, scalability, operational overhead, and cost.