After introducing the first inference benchmarks in June of 2019, today the MLPerf consortium released 595 inference benchmark results from 14 organizations. The MLPerf Inference v0.5 machine learning inference benchmark has been designed to measure how well and how quickly various accelerators and systems execute trained neural networks. The initial version of the benchmark, v0.5 currently only covers 5 networks/benchmark, and it doesn't yet have any power testing metrics, which would be necessary to measure overall energy efficiency. In any case, the benchmark has attracted the attention from the major hardware vendors, all of whom are keen to show off what their hardware can do on a standardized test, and to demonstrate to clients why their solution is superior. Of the 595 benchmark results released today, 166 are in the Closed Division intended for direct comparison of systems.