---
title: "Beyond a Trillion : The Token Race"
description: "Google processes 574x more AI tokens than Microsoft Foundry. Explore the massive scale differences in AI inference: Google at 32.7 trillion daily tokens reveals the hidden scale of AI processing."
categories: ["AI","data analysis","trends"]
keywords: ["AI token processing","trillion tokens","Google AI inference","Microsoft Foundry","Together AI","open source inference","AI infrastructure scale","cloud AI comparison","Tomasz Tunguz","Theory Ventures","AI scalability metrics","inference market share"]
ai_summary: "Deep analysis of AI token processing reveals Google's dominance at 32.7 trillion daily tokens, 574x Microsoft Foundry's volume. Key insights on open-source inference capturing only 1-3% of market \u0026 agent adoption being \u003c1% of Azure workloads."
date: 2025-09-18
lastmod: 2026-07-23
canonical_url: https://www.tomtunguz.com/trillion-token-race/
author: "Tomasz Tunguz"
---


One trillion tokens per day. Is that a lot?

> "And when we look narrowly at just the number of tokens served by Foundry APIs, we processed over 100t tokens this quarter, up 5x year over year, including a record 50t tokens last month alone."

In April, Microsoft [shared a statistic](https://tomtunguz.com/earnings-microsoft-2025-04-30/), revealing their Foundry product is processing about 1.7t tokens per month.

{{< email_image src="tbv1vazmhn3y6w6hsqej" alt="Screenshot 2025-09-18 at 12.57.26 PM" width="540" height="149" >}}

Yesterday, [Vipul shared Together.ai](https://www.linkedin.com/feed/update/urn:li:activity:7373962095442264064/) is processing 2t of open-source inference daily.

In July, [Google announced a staggering number :](https://blog.google/inside-google/message-ceo/alphabet-earnings-q2-2025/#:~:text=Third%2C%20our%20products%20and%20platforms,and%20Waymo%20for%20the%20quarter.)

> "At I/O in May, we announced that we processed 480 trillion monthly tokens across our surfaces. Since then we have doubled that number, now processing over 980 trillion monthly tokens, a remarkable increase."

| Company           | Daily Tokens (trillions) | vs Microsoft |           Date |
| ----------------- | -----------------------: | -----------: | -------------: |
| Google            |                     32.7 |         574x |      July 2025 |
| Together          |                      2.0 |          35x | September 2025 |
| Microsoft Foundry |                    0.057 |           1x |     April 2025 |

Google processes 32.7t daily, 16x more than Together & 574x more than Microsoft Foundry's April volume.

From these figures, we can draw a few hypotheses :

1. Open-source inference is a single-digit fraction of inference. It's unclear what fraction of Google's inference tokens are from their open source models like Gemma. But, if we assume Anthropic & OpenAI are 5t-10t tokens per day[^1] & all closed-source, plus Azure is roughly similar in size, then open-source inference is likely around 1-3% of total inference. [^2]
2. Agents are early. Microsoft's data point suggests the agents within GitHub, Visual Studio, Copilot Studio, & Microsoft Fabric contribute less than 1% of overall AI inference on Azure.
3. With Microsoft expected to invest $80 billion compared to Google's $85 billion in AI data center infrastructure this year, the AI inference workloads of each company should increase significantly both through hardware coming online & algorithmic improvements.

> "Through software optimization alone, we are delivering 90% more tokens for the same GPU compared to a year ago."

Microsoft is squeezing more [digital lemonade from their GPUs](https://www.microsoft.com/en-us/investor/events/fy-2025/earnings-fy-2025-q4) & Google must also be doing similar.

When will we see the first 10t or 50t AI tokens processed per day? It can't be far off now.

[^1]: Estimates from thin air!

[^2]: Google & Azure at 33t tokens per day each, Together & 5 other neoclouds at roughly 2t tokens per day each, & Anthropic & OpenAI at 5t tokens per day, gives us 88t tokens per day. If we assume 5% of Google's tokens are from open-source models, that's 1.65t tokens per day, or roughly 1.9% of total inference. Again, very rough math.