Alphabet is designing a new server chip to improve the efficiency of its Gemini models.
Frozen v2
The project, internally named Frozen v2, is expected to launch in 2028, The Information reported using anonymous sources. The chip could achieve six to 10 times better efficiency than current Google AI hardware, measured by tokens generated per unit of power.
Google did not directly confirm the report in response to TechCrunch. It also did not deny it.
“Our teams are constantly researching and experimenting with new innovations to deliver maximum performance and efficiency for our users and customers,” Google told TechCrunch. “While not every project moves into production, this rigorous exploration is central to our full stack approach. By co-designing our hardware and software from the ground up, we ensure our systems are integrated and highly optimized for real-world workloads.”
AI firms are increasingly building their own chips to run internal models more efficiently and to address global shortages in computing capacity. Efficiency has become a key selling point as concerns about AI spend have dampened market euphoria. At the same time, companies are trying to reduce dependence on Nvidia, which has historically dominated the AI chip market.
In June, OpenAI announced its first custom chip, an inference processor dubbed Jalapeño. Earlier this month, it was reported that Anthropic was discussing a new chipmaking partnership with Samsung.
Investors have previously worried about Alphabet’s massive planned expenditures to build its AI strategy. Earlier this year, Google said that it plans to spend between $180 billion and $190 billion. With so much money at stake, the company needs to prove that those investments will pay off.
News of the more efficient Frozen v2 chip appears to have assuaged investors, giving Google a boost ahead of its earnings report later this week. Following publication of The Information’s report, the company’s stock climbed some 3% on Monday morning.
What it means
Developers and users face lower power costs and potentially faster response times. The shift also reduces reliance on Nvidia hardware, giving Google more control over its infrastructure.
