mlcommons

Reference implementations of MLPerf® training benchmarks

Reference implementations of MLPerf® inference benchmarks

Croissant is a high-level format for machine learning datasets that brings together four rich layers.

Collective Knowledge (CK), Collective Mind (CM/CMX) and MLPerf automations: community-driven projects to learn how to run AI, ML, and other emerging workloads more efficiently and cost-effectively across diverse models, datasets, software, and hardware using MLPerf methodology and benchmarks.