Better Machine Learning for Everyone
Building trusted, safe, and efficient AI requires better systems for measurement and accountability. MLCommons’ collective engineering with industry and academia continually measures and improves the accuracy, safety, speed, and efficiency of AI technologies.
MLCommons Members and Affiliates
MLPerf Performance Results to-date
Accelerating Machine Learning Innovation
In collaboration with our 125+ founding members and affiliates, including startups, leading companies, academics, and non-profits from around the globe, we democratize machine learning through open industry-standard benchmarks that measure quality and performance and building open, large-scale, and diverse datasets to improve AI models.
We help to advance new technologies by democratizing machine learning adoption through the creation and management of open useful measures of quality and performance, large scale open data sets, and ongoing research efforts.
Benchmarks help balance the benefits and risks of AI through quantitative tools that guide effective and responsible AI development. They provide consistent measurements of accuracy, safety, speed, and efficiency which enable engineers to design reliable products and services and help researchers gain new insights to drive the solutions of tomorrow.
Evaluating AI systems depends on rigorous, standardized test datasets. MLCommons builds open, large-scale, and diverse datasets and a rich ecosystem of techniques and tools for AI data, helping the broader community deliver more accurate and safer AI systems.
Open collaboration and support with the research community helps accelerate and democratize scientific discovery. MLCommons shared research infrastructure for benchmarking, rich datasets and diverse community, help enable the scientific research community to derive new insights for new breakthroughs in AI, for the betterment of society.
MLCommons is supported by our 125+ founding members and affiliates, including startups, leading companies, academics, and non-profits from around the globe.
Join Our Community
MLCommons is a community-driven and community-funded effort. We welcome all corporations, academic researchers, nonprofits, government organizations, and individuals on a non-discriminatory basis. Join us!
New benchmarks, new submitters, performance gains, and new hardware add scale to latest MLCommons MLPerf results
The initial focus will be on the development of safety benchmarks for large language models used for generative AI — using Stanford’s groundbreaking HELM framework.
Factories need good roads to deliver value