NVIDIA's AI GPU Evolution: A100 to Blackwell and What Each Generation Delivered

NVIDIA's GPU lineup has evolved significantly over recent years, with each generation targeting the growing demands of AI infrastructure. The A100, originally designed for scientific computing, became the foundation of modern AI infrastructure almost by accident, and remains useful for smaller, cost-sensitive workloads. The H100 was the first chip purpose-built for transformer models, introducing FP8 precision and becoming the dominant hardware for large language model training through 2023–2024. The H200 kept the same compute core as the H100 but nearly doubled memory capacity to 141GB of HBM3e, directly addressing memory-bound inference bottlenecks. The latest Blackwell generation shifts the paradigm further, treating the entire rack as a single compute unit, with up to 288GB of GPU memory, new NVFP4 precision, and high-bandwidth rack-scale interconnects — though these systems demand liquid cooling and over 100 kilowatts of power per rack.