gpupartner.com — Workload
Hardware for training LLMs.
Pre-training and full fine-tuning push memory, bandwidth, and interconnect harder than anything else in the AI hardware landscape. The right answer ranges from a single 8× H200 node up through GB200 NVL72 clusters depending on model size, dataset, and timeline.
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Tell us the model scale you're targeting (13B / 70B / 200B+), the dataset volume, and how long you have. We'll talk through the trade-offs honestly, sometimes the right call is fewer bigger nodes, sometimes more smaller ones, sometimes cloud for the burst.