LLM · Large Language Model
An autoregressive transformer trained on text at scale; its training and inference shapes drive the facility designs in this guide.
Current numbers
30%peak grid-demand reduction demonstrated while training Megatron-LLM with energy-enhanced power shelves
~30–50%typical model-FLOPS-utilization (MFU) for large LLM training; best-in-class >50% on Hopper
~43.4%large-LLM-job failure rate (~37% hardware-attributed; ~73% recoverable via restart)