tech
March 26, 2026
Google's TurboQuant AI-compression algorithm can reduce LLM memory usage by 6x
TurboQuant makes AI models more efficient but doesn’t reduce output quality like other methods.
TL;DR
- TurboQuant is a new AI compression algorithm developed by Google Research.
- It aims to reduce the memory footprint and boost the speed of large language models (LLMs).
- TurboQuant achieved an 8x performance increase and a 6x memory reduction in early tests without losing accuracy.
- The algorithm utilizes a two-step process: PolarQuant for converting vectors to polar coordinates and QJL for error correction.
- TurboQuant can be applied to existing models without additional training, quantizing the key-value cache to as low as 3 bits.
- This technology could make AI models less expensive to run and improve mobile AI performance.
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