Google: Cloud Order Backlog Nearly Doubled From Previous Quarter, Gemini 3.5 Pro to Launch in June
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Alphabet disclosed Wednesday that its cloud backlog topped $460 billion, nearly doubling from last quarter; AI products are scaling across the board and Gemini 3.5 Pro is expected in June — signaling AI is shifting from experimentation into revenue delivery.
What does a $460 billion backlog actually tell us?
Alphabet's cloud backlog nearly doubled quarter-on-quarter, surpassing $460 billion.
The company expects over 50% of that backlog to convert into recognized revenue within 24 months.
This means → these aren't just paper contracts. More than half will turn into real revenue within two years, showing clients are deploying, not window-shopping.
In plain terms = cloud has moved from "impressive bookings" to "confirmed cash flow."
How fast is AI usage actually growing?
Alphabet now processes over 3 trillion tokens per day; its products and platforms handle 3.2 quadrillion tokens per month.
Tokens — the smallest units a large language model processes, roughly equivalent to a short chunk of text — are the core measure of how much AI is actually being used.
This means → usage has left the experimental tier and entered industrial scale. Google's AI infrastructure is being called on massively.
User growth and cost cuts — which signal matters more?
AI Overview now has over 2.5 billion monthly active users; Gemini app MAUs topped 900 million in May, up from 400 million a year ago.
AI subscription plans are performing "exceptionally well," while Gemini's serving cost has fallen 78%.
This means → users doubling while costs drop sharply is the classic formula for AI profitability — the larger the scale, the lower the unit cost.
In plain terms = more people are using it, and each one costs less to serve. That is the healthiest growth pattern for a platform business.
Gemini 3.5 Pro launching in June — what does that signal?
Alphabet expects Gemini 3.5 Pro to launch in June.
This reflects Google maintaining a rapid iteration pace on large models, keeping step with OpenAI and Anthropic release cycles.
This means → for cloud customers, choosing Google Cloud locks in continuously upgrading AI capabilities. For rivals, the model arms race shows no sign of slowing.
Content is for reference only, not financial advice.