Use Case

Model Training

Training large language models and other deep learning architectures is compute-intensive and highly sensitive to inter-GPU communication bandwidth. High-memory GPUs with fast NVLink or Infinity Fabric interconnects reduce gradient synchronisation overhead in multi-node runs. Provider choice affects not just per-hour cost but cluster topology, networking fabric, and storage throughput — all of which influence effective training throughput. This page links the GPUs and providers most relevant to training workloads.