Google Is Building a Chip That Bakes Gemini's Architecture Into Silicon

Google is developing a server accelerator, internally called Frozen v2, that would permanently implement parts of the Gemini model architecture in hardware rather than running it as software on a general-purpose chip, according to reporting from The Information relayed by CNBC and TechCrunch. The name describes the design, because the model's computing logic is fixed permanently into the silicon. Alphabet shares rose after the report.

The key technical distinction is that Frozen v2 hardwires the architecture, not the weights. New Gemini weights can still be loaded, as long as future models keep the same underlying structure. Google engineers estimate the part could serve between six and ten times more tokens per unit of power than the company's latest tensor processing units (TPUs), The Decoder reported. That efficiency comes at the cost of generality, because an application-specific integrated circuit (ASIC) tuned to one architecture becomes useless the moment the architecture changes.

Several caveats limit the claim. Google reportedly views Frozen v2 as a trial run rather than a TPU-scale program, with deployment expected around 2028. The projections are internal and unverified by independent benchmarks, and no silicon has been shown. What matters is the direction. A large cloud company is judging that model architectures are now stable enough to justify fixing them into hardware for the inference workloads that dominate its serving costs.