Logan Kilpatrick says Google processed about 25 trillion tokens with Gemini 4 Argon in the first 72 hours after launch
In just the first 72 hours since Gemini 4 Argon launched, we processed ~25 trillion tokens, the demand for intelligence is incredible and still under appreciated!
Context
Early usage on that scale suggests strong demand for Google's newest model and heavy load on its compute.
Logan Kilpatrick works on Gemini, Google AI Studio and the Gemini API at Google, so this is a first hand figure, though Google gave no breakdown. Gemini 4 Argon is Google's latest flagship model, covered in several recent decks.
Deep dive
Shortly after midnight on October 21, Logan Kilpatrick posted that in just the first 72 hours since Gemini 4 Argon launched, Google processed about 25 trillion tokens. He said the demand for intelligence is incredible and still under appreciated.
A token is a small chunk of text, roughly three quarters of a word on average in English, so 25 trillion tokens is a very large amount of input and output. Spread evenly, it would be more than 8 trillion tokens a day.
He did not say whether the figure covers only the API and AI Studio or also the Gemini app, how much was input versus output, or how it compares with earlier Gemini launches. Without that, the number is hard to compare with figures other labs have shared.
Google has spent the days since launch promoting Argon with demos built in its Antigravity coding tool, such as a 3D fur engine, a Wizard Chess game and a periodic table, and expanded access to Google AI Pro subscribers in AI Studio.
Token counts are a common way for labs to signal demand, and they also reflect how much compute a model is using.
What to expect next
Watch for Google to share fuller usage numbers for Gemini 4 Argon, for example on its next earnings call, including how they compare with earlier Gemini models. Rate limits or capacity problems would show whether demand is straining its compute. Also watch whether OpenAI and Anthropic respond with usage figures of their own for their latest models. Developers' reports of speed and reliability will add context to the figure.