The MLPerf Automotive benchmark suite measures the performance of computers intended for automotive, both for Advanced Driving Assistance System/Autonomous Driving (ADAS/AD) and In-Vehicle Infotainment (IVI) embedded systems.| MLCommons
AVCC® and MLCommons® announced new results for their new MLPerf® Automotive v0.5 benchmark| MLCommons
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New checkpoint benchmarks provide “must-have” information for optimizing AI training The post New MLPerf Storage v2.0 Benchmark Results Demonstrate the Critical Role of Storage Performance in AI Training Systems appeared first on MLCommons.| MLCommons
MLCommons, MLPerf Storage v2.0 Addressing Backup and Recovery Speed for Training Large Language Models on Scale-Out Clusters| MLCommons
MLCommons Releases MLPerf Client v1.0 with Expanded Models, Prompts, and Hardware Support, Standardizing AI PC Performance.| MLCommons
The MLCommons Croissant working group standardizes how ML datasets are described to make them easily discoverable and usable across tools and platforms.| MLCommons
The Mobile working group creates a set of fair and representative inference benchmarks for mobile consumer devices such as smartphones, tablets, and notebooks that is representative of the end user experience.| MLCommons
MLCommons Launches MLPerf Mobile on Google Play Store| MLCommons
Fostering a community of talented young researchers at the intersection of ML and systems research The post Introducing the 2025 MLCommons Rising Stars appeared first on MLCommons.| MLCommons
MLCommons President Peter Mattson joined industry leaders and experts to discuss the road forward for responsible AI innovation at the Asia Tech x summit in Singapore. The post Peter Mattson Joins Leaders to Discuss AI Innovation at Asia Tech x Conference in Singapore appeared first on MLCommons.| MLCommons
MLCommons AAAI 2025 standardization collaboration evaluation in ai safety| MLCommons
The website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address.| mlcommons.org
MLCommons and partners unite to create actionable reliability standards for next-generation AI agents.| MLCommons
More submissions, new hardware accelerators, and more multi-node systems The post New MLCommons MLPerf Training v5.0 Benchmark Results Reflect Rapid Growth and Evolution of the Field of AI appeared first on MLCommons.| MLCommons
World leader in AI benchmarking announces new partnership with India’s NASSCOM; updated reliability grades for leading LLMs The post MLCommons Announces Expansion of Industry-Leading AILuminate Benchmark appeared first on MLCommons.| MLCommons
MLCommons adds new pretraining benchmark for testing large-scale systems The post MLCommons MLPerf Training Expands with Llama 3.1 405B appeared first on MLCommons.| MLCommons
CKAN supports the MLCommons Croissant metadata standard| MLCommons
Research funded through a grant by MLCommons and published by the Open Data Institute and the Pratt School of Engineering at Duke University explores the motivations driving data sharing throughout the AI ecosystem.| MLCommons
MLCommons aims to accelerate AI innovation to benefit everyone. It's philosophy of open collaboration and collaborative engineering seeks to improve AI systems by continually measuring and improving the accuracy, safety, speed and efficiency of AI technologies. We help companies and universities around the world build better AI systems that will benefit society.| MLCommons
MLPerf Inference Datacenter Round 4.0 Date of Change Result ID Submitter Type of Change Reason for Change 8/28/24 4.0-0038 Dell Results invalidated Submitted as “preview,” but validation results were not submitted to “available” in the subsequent round. 8/28/24 4.0-0050 HPE Results invalidated Submitted as “preview,” but validation results were not submitted to “available” in the subsequent round. 8/28/24 4.0-0059 Lenovo Results invalidated Submitted as “preview,” but vali...| MLCommons
Announcing the release of the MLComons AI Safety v0.5 benchmark proof-of-concept focusing on measuring the safety of LLMs| MLCommons
The MLPerf Benchmark Suites measures how fast machine learning systems can train models to a target quality metric using v2.0 results.| MLCommons
