NVIDIA GPUs
The default GB300 / GB200 / B200 / B100 / H200 / H100 with FP8, NVLink, and InfiniBand.
AMD GPUs
ROCm 6.3+ with patches for virtual memory management. Same launch scripts.
Supported features by GPU
Storage and network
Independent of GPU vendor, you’ll want:- Shared filesystem for multi-node — NFS, GPFS, Lustre. Reads dominate writes during training; provision read bandwidth.
- High-bandwidth interconnect — IB (NVIDIA), RoCEv2 (NVIDIA), Slingshot, or Infinity Fabric (AMD). 200+ GB/s per node is typical for trillion-param training.
- NVMe local scratch for SGLang radix cache and Ray spill — at least 1 TB.

