The foundation for MLCommons started with the MLPerf benchmarks in 2018, which established industry-standard metrics to measure machine learning performance and quickly grew to encompass data sets and best practices. The MLPerf benchmarks played a critical role for industry and research and were tremendously popular. The community quickly spread across nearly every continent and grew to over 70 supporting organizations from software startups, to researchers at top universities, and to cloud computing and semiconductor giants.

From the beginning, we knew that to drive progress in machine learning, we needed benchmarks that pushed on the frontier between research and industrial practice and that creating large-scale open data sets would be critical to shifting this line over time. To democratize these newfound technological capabilities and ensure wide adoption, we needed to reduce friction and improve ML portability so that we could share best practices across the boundaries between countries, between academia and industry, and between researchers and engineers in companies. This gave birth to our three pillars and the mission of MLCommons, which we formed in 2020. Some key milestones in our history include: