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Google’s TurboQuant algorithm slashes the memory bottleneck that limits how many AI models can run at once

Running a large language model is expensive, and a surprising amount of that cost comes down to memory, not computation.

Google's new TurboQuant algorithm speeds up AI memory 8x, cutting costs by 50% or more

Within 24 hours of the release, community members began porting the algorithm to popular local AI libraries like MLX for Apple Silicon and llama.cpp.