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Training and fine-tuning large language models from 7B to 70B+ parameters. AIMC scores this specific combination 100/100 — excellent fit.
Excellent fit. AIMC's fit score combines VRAM headroom, GPU class match, and FP16 compute against the workload's requirements — independent of pricing.
Listing-weighted median across 3 observed H100 NVL listings at AIME. The same GPU is tracked at 6 marketplaces total.
Top 5 alternative providers for the same GPU, sorted by price ascending.
Alternative high-fit options at the same provider, sorted by fit score.
Training and fine-tuning large language models from 7B to 70B+ parameters. LLM Training requires at least 24 GB VRAM and benefits from Datacenter-class compute.
Full LLM Training guide and all viable GPUsGet alerts when AIME adjusts pricing on the H100 NVL — useful for sustained llm training workloads.