Methods and apparatus are disclosed for providing emulation of quantized precision operations. In some examples, the quantized precision operations are performed for neural network models. Parameters of the quantized precision operations can be selected to emulate operation of hardware accelerators adapted to perform quantized format operations. In some examples, the quantized precision operations are performed in a block floating-point format where one or more values of a tensor, matrix, or vectors share a common exponent. Techniques for selecting the exponent, reshaping the input tensors, and training neural networks for use with quantized precision models are also disclosed. In some examples, a neural network model is further retrained based on the quantized model. For example, a normal precision model or a quantized precision model can be retrained by evaluating loss induced by performing operations in the quantized format.
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