Cheaper AI Tokens Fuel Demand as Jevons' Paradox Plays Out in GPU Market

Token Prices Fall, GPU Rental Costs Hold

Cheaper AI tokens are driving more demand, a scenario Jensen Huang would welcome. Data from Ornn, Silicon Data, and Bloomberg, current through August 2026, shows token prices continuing to drop while H100 GPU rental prices hold steady or climb. According to a16z, the pattern is a textbook example of Jevons' paradox, in which falling per-unit costs cause overall consumption to grow faster than prices decline.

Agents and Automation Unlock New Demand

Lower token prices are unlocking AI agents, automation, and new applications, pushing volume growth ahead of per-unit cost declines. How much of that demand comes from humans versus the systems themselves remains unclear, since agentic AI burns through tokens at a staggering rate. Compute demand could be artificially inflated, meaning even modest human usage growth could trigger outsized hardware needs.

The Fragile Assumption Behind the Boom

The whole system rests on one assumption: AI usage has to grow fast enough to offset falling token prices. As long as it does, hardware stays scarce and expensive. If demand flattens, the chain from chip makers and memory suppliers to energy providers and cloud companies takes a hit, and markets could spiral from there. How sensitive markets already are became clear when US stocks dropped on reports that OpenAI's annualized revenue might be lower than previously reported.

Sources: The Decoder