@SanDisk, @simplyblock_io, TTA, UBIX, @westerndigital, & YanRong. See the full results and learn more at #MLPerf #AI #Storage #Benchmarking #MachineLearning #MLCommons.

5/ Congratulations to all submitters! .@Alluxio, @argonne, @DDNintelligence, ExponTech, FarmGPU, @H3CGlobal, @Hammerspace_Inc, @HPE, JNIST/ @Huawei , @IBM, @kingstontech, @KIOXIAAmerica , @LightbitsLabs, @MangoBoost_Inc, @MicronTech , @nutanix, @Oracle, @QuantaQCT, @Samsung,.

4/ The v2.0 submissions showcase a wide range of technical solutions—local & object storage, in-storage accelerators, software-defined storage, block systems, and more. This diversity highlights the community’s commitment to advancing AI infrastructure.

3/ New in this round: checkpoint benchmarks, designed to reflect real-world practices in large-scale AI training systems. These benchmarks provide key data to help stakeholders optimize system reliability and efficiency at scale.

2/ v2.0 highlights:.- 200+ results.- 26 organizations.- 7 countries represented.- Benchmarked systems now support about 2x the accelerators vs v1.0.

1/ MLCommons just released results for the MLPerf Storage v2.0 benchmark—an industry-standard suite for measuring storage system performance in #ML workloads. This benchmark remains representative, reproducible, and architecture-neutral.

MLPerf Client v1.0 is out! 🎉. The new benchmark for LLMs on PCs and client systems, available now—featuring expanded model support, new workload scenarios, and broad hardware integration. Thank you, submitters! @AMD , @intel , @Microsoft, @nvidia , @Qualcomm

Great insights from @DavidKanter of @MLCommons on how MLPerf measures AI data storage performance. 🔜 MLPerf Storage v2.0 drops 8/4!.#MLPerf #AI #DataStorage #MLCommons.

RT @ApertureData: 🥐 Summer of Workflows: Release #1 is here!. Introducing Workflow #1: Croissant Ingestion.A ready-to-run tool that ingest….

You can read more details here:

MLCommons® just launched MLPerf® Mobile on the Google Play Store! 📱 .Benchmark your Android device’s AI performance on real-world ML tasks with this free, open-source app. Try it now:

3/3 Read more about the collaborative development of the Agentic Reliability Evaluation Standard and opportunities to participate:

2/3 Contributors from: @AdvaiLtd , AI Verify Foundation, @AnthropicAI , @arizeai , @cohere , @Google , @intel , @LNE_fr , @Meta , @Microsoft , @nasscom , @OpenAI , @PatronusAI, @polymtl , @Qualcomm , @quantumblack - AI by McKinsey, @salesforce , Schmidt Sciences, @ServiceNow ,.

Today, MLCommons is announcing a new collaboration with contributors from across academia, civil society, and industry to co-develop an open agent reliability evaluation standard to operationalize trust in agentic deployments. 1/3.🔗

RT @algoperf: We're all about acceleration! 😉.Watch @KasimbegPriya & @frankstefansch1 speedrun an explanation of the AlgoPerf benchmark, ru….

RT @nasscomai: 📰 #InTheNews @nasscom calls for a new tier of trust for #AgenticAI in India. @ankitthe1 says risks go beyond hallucinations—….

RT @charvvvv_: Join @MLCommons for a social at @FAccTConference 2025, where we're tackling the critical need for a unified and collective a….

Companies are deploying AI tools that haven't been pressure-tested, and it's already backfiring. In her new op-ed, our President, Rebecca Weiss, discusses how industry-led AI reliability standards can help executives avoid costly, high-profile failures. 📖 More:.

2/ Thank you to all 20 submitters:.@AMD , @ASUS , @Cisco , @CoreWeave , @Dell , @GigaComputing , @Google Cloud, @HPE , KRAI, @LambdaAPI , @Lenovo , @MangoBoost_Inc , @nebiusai , @nvidia , @Oracle , @QuantaQCT, @scitix , @Supermicro_SMCI , @__tinygrad__ .