BitcoinWorld Google is developing a new AI chip to make Gemini far more efficient Alphabet, Google’s parent company, is designing a new server chip internally dubbed “Frozen v2” to help its in-house Gemini AI models operate more efficiently, according to a report from The Information published Monday. The chip is slated for release sometime in …
BitcoinWorld
Google is developing a new AI chip to make Gemini far more efficient
Alphabet, Google’s parent company, is designing a new server chip internally dubbed “Frozen v2” to help its in-house Gemini AI models operate more efficiently, according to a report from The Information published Monday. The chip is slated for release sometime in 2028 and could be between six and ten times more efficient than Google’s existing AI chips, measured by the number of tokens generated per unit of power.
Google did not directly confirm the report but did not deny it either. In a statement to Bitcoin World, a company spokesperson said: “Our teams are constantly researching and experimenting with new innovations to deliver maximum performance and efficiency for our users and customers. 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.”
The development comes as major AI companies increasingly seek to produce their own chips to make their in-house models run more efficiently and to address global shortages in AI computing capacity. Efficiency has become a key selling point for tech companies as concerns about AI spending have dampened the market euphoria that previously characterized the industry.
Firms are engaged in an ongoing effort to reduce their dependence on chipmaker Nvidia, which has historically dominated the AI chip market. In June, OpenAI announced its first custom chip, an inference processor called 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 out its AI strategy. Earlier this year, Google said 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 approximately 3% on Monday morning.
The push for custom chips is not just about performance—it’s about controlling costs and supply chains. By designing its own silicon, Google can optimize hardware specifically for its workloads, potentially reducing energy consumption and operational expenses. For readers, this means more capable AI services at lower costs, and a more competitive landscape that could accelerate innovation across the industry.
Google’s Frozen v2 chip represents a significant step in the company’s long-term AI hardware strategy. While still years away from production, the reported efficiency gains could reshape how AI models are deployed at scale. The move also underscores a broader industry trend toward vertical integration in AI hardware, as major players seek to reduce reliance on Nvidia and gain greater control over their AI infrastructure.
Q1: What is the Frozen v2 chip?
A1: Frozen v2 is a new server chip reportedly being designed by Alphabet, Google’s parent company, to make its Gemini AI models more efficient. It is expected to be released around 2028.
Q2: How much more efficient is Frozen v2 compared to Google’s current chips?
A2: According to The Information, the chip could be between six and ten times more efficient, measured by the number of tokens generated per unit of power.
Q3: Why are AI companies developing their own chips?
A3: AI companies are designing custom chips to improve efficiency, reduce dependence on Nvidia, address global AI computing shortages, and lower operational costs. This trend includes efforts by OpenAI, Anthropic, and Google.
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Eloise J. Coward is a crypto enthusiast turned investigative writer, known for her deep dives into Web3 ecosystems, smart contract vulnerabilities, and blockchain forensics. A former cybersecurity analyst, Eloise brings a technical edge to her articles, making even the most complex crypto topics accessible. She thrives on decoding scams and spotlighting ethical innovation in the space.
