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This repository is the research home: the Python reference implementation, the validation papers, and the benchmark data. To run TurboQuant in an inference ...
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Cumulative release since tqp-v0.3.0. This is a large one, with major KV streaming, MoE paging, backend performance, and model support work.
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The main goal of llama.cpp is to enable LLM (and VLM) inference with minimal setup and state-of-the-art performance on a wide range of hardware - locally and in ...
2026/4/8 -A collection of TurboQuant+ compressed models designed to improve quality at practical memory limits. TurboQuant+ applies tensor-aware ...
2026/5/4 -TurboQuant Plus focuses on experimentation and performance tuning, allowing developers to test different configurations and evaluate trade-offs.
2026/3/27 -turboquant_plus is closer to making a real C implementation, but neither repo actually has a complete working C implementation yet. Here's the ...