---
title: "Is Token Consumption Growth Slowing Down?"
description: "Google's AI token processing reaches 1.3 quadrillion monthly tokens in October 2025, but growth decelerates from 250T to 107T per month. What's driving the slowdown?"
categories: ["AI","data analysis","infrastructure"]
keywords: ["AI token processing deceleration","Google AI growth slowdown","token growth analysis","AI infrastructure investment","cloud AI scaling","inference workload trends","hyperscaler capacity constraints","Tomasz Tunguz","Theory Ventures"]
ai_summary: "Google's token processing hits 1.3 quadrillion in October 2025, but monthly growth rate drops 57% from 250T to 107T, signaling potential AI infrastructure maturation amid $400B data center buildout."
date: 2025-10-10
lastmod: 2026-07-23
canonical_url: https://www.tomtunguz.com/is-token-consumption-slowing-down/
author: "Tomasz Tunguz"
---


Philip Schmid dropped an astounding figure[^1] yesterday about Google's AI scale : 1,300 trillion tokens per month (1.3 quadrillion - first time I've ever used that unit!).

{{< email_image src="ngvpk0blqc9dgfldhzue" alt="Google's Token Growth Is Slowing" width="540" height="304" >}}

Now that we have three data points on Google's token processing, we can chart the progress.

In May, Google announced at I/O[^2] they were processing 480 trillion monthly tokens across their surfaces. Two months later in July, they announced[^3] that number had doubled to 980 trillion. Now, it's up to 1300 trillion.

The absolute numbers are staggering. But could growth be decelerating?

{{< email_image src="pmrohkrpfmmyofq7hzwz" alt="Google's Monthly Token Growth Deceleration" width="540" height="304" >}}

Between May & July, Google added 250T tokens per month. In the more recent period, that number fell to 107T tokens per month.

This raises more questions than it answers. What could be driving the decreased growth? Some hypotheses :

1. Google may be rate-limiting AI for free users because of unit economics.

2. Google may be limited by data center availability. There may not be enough GPUs to continue to grow at these rates. The company has said it would be capacity constrained through Q4 2025 in earnings calls this year.

3. Google combines internal & external AI token processing. The ratio might have changed.

4. Google may be driving significant efficiencies with [algorithmic improvements, better caching, or other advances](https://tomtunguz.com/input-output-ratio/) that reduce the total amount of tokens.

I wasn't able to find any other comparable time series from neoclouds or hyperscalers to draw broader conclusions. These data points from Google are among the few we can track.

Data center investment is scaling towards $400 billion this year.[^8] Meanwhile, incumbents are striking strategic deals in the tens of billions, [raising questions about circular financing & demand sustainability](https://tomtunguz.com/nvidia-nortel-vendor-financing-comparison/).

This is one of the metrics to track!

[^1]: [Philip Schmidt on X](https://x.com/_philschmid/status/1976615984858337579)
[^2]: [Google I/O May 2025](https://blog.google/inside-google/message-ceo/alphabet-earnings-q2-2025/)
[^3]: [Google Q2 2025 Earnings](https://tomtunguz.com/trillion-token-race/)
[^4]: [Beyond a Trillion : The Token Race](https://tomtunguz.com/trillion-token-race/)
[^5]: [Microsoft FY2025 Q4 Earnings](https://www.microsoft.com/en-us/investor/events/fy-2025/earnings-fy-2025-q4)
[^6]: [Fireworks AI Platform](https://fireworks.ai/)
[^7]: [Microsoft FY2025 Q4 Earnings - GPU Optimization](https://www.microsoft.com/en-us/investor/events/fy-2025/earnings-fy-2025-q4)
[^8]: [Tech megacaps plan to spend more than $300 billion in 2025](https://www.cnbc.com/2025/02/08/tech-megacaps-to-spend-more-than-300-billion-in-2025-to-win-in-ai.html), CNBC (February 2025); [Morgan Stanley: Hyperscaler capex nearing $400 billion annually](https://www.datacenterdynamics.com/en/news/morgan-stanley-hyperscaler-capex-to-reach-300bn-in-2025/)