Google TurboQuant slashes LLM inference time 90%
Google's new TurboQuant KV cache compression algorithm, recently integrated into the Ollama ecosystem via llama.cpp, is delivering massive speedups for local LLM users. A recent benchmark of the Hermes 3 8B model showed response times dropping from 45 seconds to just 5 seconds, a 9x performance gain.
TurboQuant's high-efficiency KV cache compression enables up to 6x memory reduction with near-zero accuracy loss. The 9x speedup reported in early community benchmarks highlights a massive reduction in memory bandwidth overhead for local models. While integration into the llama.cpp backend is early, the training-free PolarQuant approach makes the technology universally applicable to transformer models like Llama 3.1 and Hermes 3.
DISCOVERED
56d ago
2026-04-01
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56d ago
2026-04-01
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