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Amazon SageMaker model training now supports heterogeneous clusters, which enables launching training jobs that use multiple instance types in a single job. This new capability can improve your training cost by running different parts of the model training on the most suitable instance type. For example, we recently trained a ResNet-50 computer vision model on a heterogeneous cluster with ml.g5.xl and ml.c5n.2xl instances. This training job resulted in 13% lower cost than training the same model on a cluster with only ml.g5.xl instances with the same accuracy.

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