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Reka Quant is compatible with any quantization primitive and leverages calibrated error reduction together with direct self-distillation to deliver state-of-the-art performance at low bitwidths. This blogpost details our approach to low bitwidth model quantization. Quantization primitives and error reduction Most quantization approaches can be characterized by the quantization primitive and the error reduction techniques they use. The quantization primitive is the quantization function itself, that takes a minimal block of numbers and maps it to a representation in the quantized datatype. In other words, the quantization primitive “rounds” the numbers to their quantized versions. This depends on the quantized datatype, as well as grouping strategies used to chunk numbers together to be quantized with the same quantization scales. 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