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Existing methods โ GPTQ, AWQ, llama.cpp's k-quants โ minimize empirical loss heuristically. None of them prove they are optimal in any information-theoretic sense. ICRB-Q builds a quantization scheme that is provably optimal via the Cramรฉr-Rao lower bound (CRB): no unbiased estimator of a weight can have lower variance than [F(ฮธ)]โปยน, where F is the Fisher information matrix.