Puru Saxena argues that falling AI token prices paradoxically increase total computing demand through the Jevons paradox, as cheaper inference unlocks new agentic workflows and automation. While unit costs decline, total GPU, HBM, and infrastructure spending remain elevated due to surging volume, supporting AI hardware makers and infrastructure stocks despite margin pressures on hyperscalers.
Puru Saxena argues that falling token prices amid high GPU costs exemplify the Jevons paradox: cheaper inference costs drive explosive growth in AI compute demand, keeping hardware resources scarce. This benefits GPU makers and infrastructure providers despite unit price declines, as total spending and capacity utilization remain elevated.