GPU Clusters for AI Model Training

Training jobs need many GPUs working as one, which makes interconnect, storage throughput and contract terms as important as the GPU model.

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By the RentServers team at Wells Software Consulting LLC · Updated October 16, 2026

Recommended setup

GPU	H100 for cost-sensitive training; B200 when time-to-result matters and your stack supports Blackwell
Interconnect	400 Gb/s InfiniBand or RoCE per GPU for multi-node jobs
Storage	Parallel file system or high-throughput object storage close to the cluster
Term	Reserved, matched to your training schedule

Start from memory: mixed-precision Adam needs roughly 16 bytes per parameter before activations, so a 70B model needs at least 16 80 GB GPUs. Then work out GPU-hours from your token budget and expected utilization, and compare on-demand against a reservation.

Before a reservation starts, run NCCL all-reduce tests across nodes and a short version of your real job to confirm throughput.

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