Why Google’s New AI Chip Is the Key to Unlocking Its Massive $462 Billion Backlog
Google Cloud's $462 billion backlog, exceeding 10x its 2025 revenue, highlights massive AI demand but also compute constraints that forced Alphabet to reject capacity requests from major customers including Meta. To address this, Google is developing Frozen v2, a specialized server chip that hardwires key portions of the Gemini AI model architecture directly into silicon. Engineers project Frozen v2 could deliver 6 to 10 times more tokens per unit of power than current TPUs, with deployment targeted for 2028. Alphabet's full-stack control over chips, software, and models has already driven Google Cloud's operating margin from 18% to 33%. The company raised 2026 capital expenditure guidance to $180-190 billion to expand data centers and custom chips, aiming to convert the massive backlog into sustained revenue growth.
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Why Google’s New AI Chip Is the Key to Unlocking Its Massive $462 Billion Backlog
Google Cloud's $462 billion backlog, exceeding 10x its 2025 revenue, highlights massive AI demand but also compute constraints that forced Alphabet to reject capacity requests from major customers including Meta. To address this, Google is developing Frozen v2, a specialized server chip that hardwires key portions of the Gemini AI model architecture directly into silicon. Engineers project Frozen v2 could deliver 6 to 10 times more tokens per unit of power than current TPUs, with deployment targeted for 2028. Alphabet's full-stack control over chips, software, and models has already driven Google Cloud's operating margin from 18% to 33%. The company raised 2026 capital expenditure guidance to $180-190 billion to expand data centers and custom chips, aiming to convert the massive backlog into sustained revenue growth.