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MLPerf Client

Place
#34 of 70
Score
6.8
MLPerf Client's website

The facts below are what the maker publishes about MLPerf Client, checked and dated. Our editors have not written about it yet.

The facts

Each one read from MLPerf Client's own pages, with the date it was checked.

What it does

Agentic AI
Agentic tests cover Software Engineering and Data Analyst tasks and measure end-to-end duration, including LLM inference and tool execution.checked 9 Oct 2026
CLI or automation
Yeschecked 23 Sep 2026
Custom test profiles
Yeschecked 23 Sep 2026
Download and source
The benchmark is downloadable from its GitHub release page, and its public GitHub repository contains source code that users may inspect or modify.checked 8 Oct 2026
Downloads
The benchmark is downloadable from GitHub, its iPad version is available in Apple's App Store, and its public GitHub repository contains source code.checked 9 Oct 2026
Experimental components
The Linux CLI version, power-efficiency tools, Flux 2 Klein 4B image generation, and some agentic workloads are identified as experimental.checked 8 Oct 2026
Hardware limits
The benchmark requires 200GB of free drive space and recommends 400GB to run all models; minimum hardware and memory requirements vary by platform.checked 8 Oct 2026
Hardware requirements
Minimum hardware requirements list selected AMD, Intel, NVIDIA, Qualcomm, and Apple systems, with memory and VRAM requirements varying by platform.checked 9 Oct 2026
Image generation
The image generation test uses the experimental Flux 2 Klein 4B model and reports images per minute at 1024×1024 resolution.checked 9 Oct 2026
Internet use
An internet connection is needed for the first run with an acceleration path; downloaded files are stored locally for later runs.checked 8 Oct 2026
LLM workloads
Its LLM tasks include creative writing, content generation, structured text, code analysis, and summarization, using models including Llama 3.1 8B Instruct and Phi 4 Mini Instruct.checked 9 Oct 2026
Network use
An internet connection is needed for the first run with an acceleration path to download files; later runs use locally stored files.checked 9 Oct 2026
Operating systems
Windows 11; macOS Tahoe 26; iPadOS 26; Ubuntu Linux 24.04checked 23 Sep 2026
Purpose
MLPerf Client benchmarks LLM, generative image, and agentic AI performance on personal computers, including laptops, desktops, and workstations.checked 9 Oct 2026
Quality checks
The working group applies MMLU and IFEval accuracy requirements to qualify accelerated execution paths and models for release.checked 9 Oct 2026
Result export formats
CSVchecked 23 Sep 2026
Result validity
Only scores produced with configurations marked “Configuration tested by MLCommons” are considered valid MLPerf Client scores.checked 8 Oct 2026
Scoring limits
Only base components can contribute to an official MLCommons-tested score; extended and experimental results are marked separately.checked 9 Oct 2026
Storage requirement
The benchmark requires 200GB of free drive space and recommends 400GB to run all models.checked 9 Oct 2026
Support
Users can submit questions, feature requests, or problems through the support form for working-group review and response as needed.checked 9 Oct 2026
Supported systems
The stated operating system requirements are Windows 11, macOS Tahoe 26, iPadOS 26, or Ubuntu Linux 24.04; Linux is described as CLI-only and experimental.checked 9 Oct 2026

Money

Free plan
Yeschecked 23 Sep 2026

The company

Maker
MLCommons describes itself as an open AI engineering consortium that develops benchmarks through collaboration between industry and academia.checked 9 Oct 2026
Maker history
MLCommons' history page lists its launch as December 3, 2020.checked 9 Oct 2026

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