Google unveils TurboQuant, shrinking AI working memory by at least 6x
A new compression algorithm cuts the memory AI models use while running. The internet is already calling it "Pied Piper."
What is TurboQuant?
Google Research announced TurboQuant, a compression algorithm for the "working memory" of AI models, known as the KV cache.
Google says that, if implemented, it can reduce that memory by at least 6x.
How it works
- It uses vector quantization.
- It introduces two methods: PolarQuant and QJL.
- It will be presented at ICLR 2026.
"Pied Piper"
People online compared it to Pied Piper, the fictional compression startup from HBO's Silicon Valley.
Cloudflare CEO Matthew Prince called it "Google's DeepSeek moment."
Key caveats
- It is still a lab result, not broadly deployed.
- It only targets memory used during inference, not training.
- So it won't fix the global RAM shortage driven by AI.
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