GPU cost is the underlying compute cost of training and running AI models, dominated by Nvidia's H100, H200, B200, and B300 chips at $25,000-$50,000 each. GPU availability and cost are the limiting factor for AI training because foundation model labs need thousands of GPUs running together in clusters. The GPU supply chain is the single largest infrastructure story of the 2020s tech boom. Behind every AI capability is a stack of expensive GPUs running hot.
The Nvidia GPU lineup (mid-2026):
| GPU | Launch | Approximate price | Use case |
|---|---|---|---|
| A100 | 2020 | $10K-$15K | Legacy AI workloads |
| H100 | 2022 | $25K-$40K | Mainstream LLM training/inference |
| H200 | 2024 | $30K-$50K | Improved memory for large models |
| B100/B200 | 2024-2025 | $40K-$60K | Next-gen Blackwell... |