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Alphabet's Frozen v2 chip targets the inference overhead built into general-purpose silicon

7/26/2026

General-purpose AI accelerators are designed to execute any model architecture, and that breadth carries a cost: silicon area and power both go toward flexibility that a dedicated model never uses.

Alphabet is reported to be developing a chip called "Frozen v2" that would embed parts of Gemini's architecture directly into the hardware, and Alphabet's stock rose on the news.

The constraint that model-specific silicon addresses Every AI chip must choose how much of its compute to make programmable.

A fully programmable chip can run any model but spends cycles fetching, decoding, and routing instructions for operations that a specific model will execute in a fixed pattern every time.

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