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At Google I/O, CEO Sundar Pichai highlighted a dramatic surge in AI usage: Google now processes roughly 3.2–32 quadrillion tokens per month, a multi‑fold increase year over year, alongside strong adoption of its Gemini ecosystem. Gemini App surpassed hundreds of millions of monthly users with daily requests rising more than sevenfold, and image model usage exceeded tens of billions of generated images. Together these metrics reflect rapid scaling of model-serving infrastructure, growing reliance on multimodal generative services, and mounting pressures on cloud costs, developer tooling, moderation, and competition in large-model deployment.
Rapid token growth shows real, large-scale customer demand for AI services and strains infrastructure, cost, and governance choices. Tech professionals must plan for higher capacity, observability, and cost controls as multimodal usage expands.
Dossier last updated: 2026-05-20 04:38:15
@qinbafrank: Token消耗的爆发式增长，这次谷歌I/O大会个人最关注并不是新产品发布这些很重要，而更重要的是token消耗数据。为什么要关注token消耗数据？这个数据代表最下游B端和C端的用户需求有多大，增速有多快。看看谷歌I/O大会上皮查公布的谷歌
Charles Rollet / Business Insider : Sundar Pichai announced at Google I/O that Gemini 3.5 Pro will launch next month; attendees groaned at the model coming out later than they expected — - Google CEO Sundar Pichai announced that Gemini 3.5 Pro will launch next month. — Google I/O 2026 attendees groaned at the model coming out later than they'd expected.
Ina Fried / Axios : Sundar Pichai says Google is now processing 3.2 quadrillion tokens per month, up from 480T tokens per month a year ago and 9.7T tokens per month two years ago — Google used its I/O developer conference on Tuesday to showcase how deeply it plans to embed AI across its products …
At Google I/O 2026, CEO Sundar Pichai revealed Google now processes over 32 quadrillion tokens per month, a sevenfold year-over-year increase. The company also reported Gemini App surpassing 900 million monthly active users with daily requests up more than 7x, and its Nano Banana image model generating over 50 billion images to date. These figures highlight massive scale-up in Google’s AI infrastructure, user adoption of its multimodal assistant, and heavy demand for generative image services—signals of intensifying competition in large-model deployment, cloud costs, developer ecosystems, and content moderation challenges across the industry.