Cheaper AI Could Make Computing Power More Expensive — Grayscale

Published: October 11, 2026 – 14:30 UTC

Grayscale explained why cheaper AI could boost demand for computing power.
An analyst emphasized that AI agents consume up to 50 times more tokens than chatbots.
Goldman Sachs believes token consumption could increase 24-fold by 2030 due to the development of AI agents.

Grayscale’s head of research, Zach Pandl, explained why falling AI costs and the rise of autonomous AI agents could increase demand for computing power and the physical infrastructure required to run them.

Artificial Intelligence usage is increasing, and token consumption is expected to increase 24x by 2030.Agents, @OpenAI’s "dots," and new lower-cost models could further amplify demand for compute. But the physical infrastructure powering compute remains a bottleneck.Read more on The Stack: https://t.co/A4Pzr7Iv1W
— Grayscale (@Grayscale) October 10, 2026

In his view, expanding AI usage could outweigh gains in model efficiency and create additional opportunities for owners of scarce compute resources.

AI Agents Increase Token Consumption

According to Pandl, competition from cheaper open-weight models is driving down the cost of tokens — units of text that AI processes and generates. For example, Anthropic says its latest Sonnet model costs up to 30% less to complete a single task.

At the same time, the development of autonomous agents capable of working around the clock on a user’s goals could significantly increase compute volumes. Unlike chatbots that answer individual questions, agents carry out a sequence of actions: they analyze data, process documents, and prepare outputs.

Grayscale estimates that such workflows can consume 5 to 50 times more tokens than a typical chatbot interaction, depending on the task.

This trend is backed by data from OpenAI, OpenRouter, and Similarweb, published in an analytical report by Andreessen Horowitz’s crypto division — a16z. According to it, AI agents use nearly five times more tokens than humans, and their consumption has increased by about 14 times since February 2026.

The most active companies generate more than eight times as many tokens as typical businesses. The rise in agent usage is also affecting demand for memory and traditional automation tools.

Demand for Compute May Outpace Efficiency Gains

Pandl cites a Goldman Sachs forecast that token consumption could increase 24-fold by 2030, largely driven by the spread of agents. Even if models become more efficient, overall compute demand will keep rising if AI usage grows faster.

At the same time, digital services depend on physical infrastructure: electricity, data centers, and graphics processing units (GPUs), which take time to supply. As an example, Pandl pointed to CoreWeave, which reported signing new contracts at higher prices for compute capacity.

In Pandl’s view, cheaper AI and the development of autonomous agents will broaden the range of use cases and could intensify competition for limited compute resources. This creates potential advantages for companies that own the relevant infrastructure.

As a reminder, according to a forecast by Meta CEO Mark Zuckerberg, billions of people will be using personal AI agents over the next five years.

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Source: Incrypted