ChipsThe story, in brief
Google's "Frozen v2" chip reportedly bakes Gemini's architecture directly into silicon for efficiency gains
6-10x more efficient. Google's custom silicon play could reshape AI economics by 2028.
The KeyNews take
Why it matters
Google is moving beyond general-purpose TPUs to model-specific hardware, a strategic shift that could lock in cost advantages for Gemini inference and raise the bar for competitors' infrastructure spending.
The key facts
6 to knowChip codenamed 'Frozen v2'
Bakes Gemini architecture directly into silicon
Reported 6-10x efficiency gain vs current TPUs
Scheduled deployment: 2028
Goal: reduce AI inference costs and competitive pricing vs OpenAI/Anthropic
Source: internal sources (unverified)
Go to the source
The Decoderthe-decoder.com
Publisher excerpt: Google is developing "Frozen v2," a server chip that bakes the Gemini architecture directly into hardware. According to internal sources, it could be 6 to 10 times more efficient than current TPUs. Scheduled for 2028, the chip would drastically cut Google's AI inference costs and could give the…