Google's improvements to its Gemini AI models are boosting the company's top line.
Over the past year,
Google's business selling access to its Gemini AI models has skyrocketed, reflecting the improving quality of those models, according to three people with knowledge of Gemini's sales.
And it could also bolster
Google's still-nascent business selling software on top of those models, which has grown quickly in recent months but has garnered mixed reviews from customers.
The improvements are likely to show up in
Google's fourth-quarter earnings, which the company is scheduled to report on Feb. 4. Investors will be looking for signs that
Google is making a return on the billions it has invested in AI.
Google sells access to its models through
Google Cloud via an application programming interface. Requests sent to the Gemini API, known as API calls, more than doubled from around 35 billion in March to over 80 billion in August, according to one of the people.
The big challenge
Google still faces is persuading businesses to pay up for sophisticated software it has developed to run on top of its AI models. That software offers it a way to raise the profit margins on its AI business.
A
Google spokesperson said Gemini Enterprise has grown to 8 million subscribers across 1,500 companies, as well as over 1 million subscribers who have signed up online, a sign it is gaining ground.
"We are seeing tremendous momentum throughout our Cloud business, particularly our AI applications," a
Google spokesperson said.
But according to interviews with several customers, cloud consultants and employees, customer feedback hasn't been entirely positive. Simon Margolis, an executive at Sada, a consultant that specializes in
Google Cloud services, said the product has received mixed reviews.
In some cases, the success of
Google's Gemini models—which customers use to build their own software—may hinder its ability to sell its software built on top of them, Margolis said.
"
Google has always been much more of a builder's cloud than a 'buy a product' cloud," Margolis said. "You have a customer who could buy Gemini Enterprise or build a bunch of custom agents, and they will often choose to build."
## Gemini Rush
Google's business selling access to its models had a slow start, as its early Gemini models weren't particularly well received. But after
Google released Gemini 2.5 last spring, to enthusiastic reviews, usage surged.
So many customers, including staff at coding tool startup Cursor, wanted to use the Gemini API after the 2.5 release that
Google had to tweak how the model was delivered to make it more efficient.
There was another usage surge after Gemini 3 was released in November, also to strongly positive reviews, another of the people said.
Google has worked to improve API margins over the past year.
Google's first Gemini models, Gemini 1.0 and Gemini 1.5, had negative profit margins, meaning they cost more to operate than
Google charged for them.
Gemini 2 only sometimes had positive margins. Gemini 2.5 had positive margins, as the improved quality of the models meant
Google could compete on quality, not just price, according to the person.
As of the middle of last year,
Google's blended Gemini margins—across all models—were barely positive, far below margins on Cloud as a whole, according to another person with direct knowledge of the situation.
However, the success of the Gemini API boosted
Google's business beyond just direct API sales.
Google calculated that spending on API calls also increased spending on other
Google Cloud products.
## Gemini Enterprise
Where
Google still has work to do is in its software AI application suite, Gemini Enterprise. According to Margolis, the product has received mixed reviews all year from customers.
Niko Gruben, head of applied research at Harvey, a legal AI startup, said Gemini Enterprise was useful for him because it connected to company data. He uses it for deep research based on internal data.
Mark Shank, who leads consulting firm KPMG's business selling
Google Cloud to its clients, said 83% of KPMG employees are satisfied with Gemini Enterprise, according to internal surveys.
But according to Margolis, the consultant who specializes in
Google Cloud services, Gemini Enterprise isn't good at building custom applications.
Chirag Mehta, a principal analyst at Constellation Research, said customers told him Gemini Enterprise was good at answering shallow, general-purpose questions based on enterprise data and at generating summaries.
Still, Mehta said, the customers he talked to liked the product enough that they haven't given up on it yet, unlike with competitors like Copilot.
"People are saying, 'We're going to give it a shot,'" Mehta said.