Answer - Keras has built-in industry-strength support for multi-GPU training and distributed multi-worker training, via the tf.distribute API. However, if you have multiple GPUs on your machine, you can train your model on all of them by: Firstly, creating a tf.distribute.MirroredStrategy object. Secondly, creating and compiling your model inside the strategy’s scope. Lastly, calling fit() and evaluate() on a dataset as usual.