MLCommons
Open AI engineering consortium from industry and academia, and the publisher of MLPerf.
Also trades as MLPerf, AILuminate
About MLCommons
MLCommons is an Artificial Intelligence engineering consortium. It works with industry and academia to measure the accuracy, safety, speed, and efficiency of AI technologies. It publishes open industry-standard benchmarks that measure quality and performance. It also builds open, large-scale, and diverse datasets for AI.
MLCommons launched on December 3, 2020.
The working group includes AI industry leaders, practitioners, researchers, and civil society experts.
Drafted from mlcommons.org · not yet confirmed by MLCommons
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Recently
From MLCommons's own newsroom feed and from the hiring team.
Assessing & Managing AI Risk for Business and Commercial Deployments: A business owner’s guide to a cost you can measure, price, and manageFrom their feed
Teams managing AI risk are stuck between protecting the business and adopting it faster. Independent measurement reconciles the two. The post Assessing & Managing AI Risk for Business and Commercial Deployments: A business owner’s guide to a cost you can measure, price, and manage appeared first on MLCommons .
October 8, 2026
What Could Go Wrong When Agents Handle Your Sensitive Data? A New Taxonomy Answers.From their feed
Agents create privacy risks chatbots do not. The MLCommons Privacy Working Group's new taxonomy maps five areas of agentic data protection risk - and v0.1 is open for feedback. The post What Could Go Wrong When Agents Handle Your Sensitive Data? A New Taxonomy Answers. appeared first on MLCommons .
October 1, 2026
DLRMv4: The Next-Generation Recommendation MLPerf Training BenchmarkFrom their feed
Evolving MLPerf Training from feature-interaction baselines to production-scale sequential recommendation with HSTU and the 560 GB Yambda-5B embedding benchmark. The post DLRMv4: The Next-Generation Recommendation MLPerf Training Benchmark appeared first on MLCommons .
October 1, 2026
MLPerf Training Introduces Its First LLM Post-Training BenchmarkFrom their feed
MLPerf Training v6.1 adds an agentic reinforcement-learning workload that measures how quickly systems can teach a 397-billion-parameter language model to repair real software projects. The post MLPerf Training Introduces Its First LLM Post-Training Benchmark appeared first on MLCommons .
September 24, 2026
MLCommons Joins EU-Funded AIRIS Project to Build and Benchmark Next-Generation Biomedical AIFrom their feed
Standardizing independent evaluation, fairness, and interpretability for mechanism-informed generative AI in healthcare The post MLCommons Joins EU-Funded AIRIS Project to Build and Benchmark Next-Generation Biomedical AI appeared first on MLCommons .
September 23, 2026
Where the Industry Is Investing: A Look at MLPerf Inference v6.1From their feed
In this analysis, MLPerf Inference Working Group chairs Miro Hodak and Frank Han break down a record field of 30 submitters and 120 systems, the arrival of agentic and end-to-end benchmarks, and what the results signal about where inference engineering is headed. The post Where the Industry Is Investing: A Look at MLPerf Inference v6.1 appeared first on MLCommons .
September 17, 2026