MLPerf Client

Personal Computer AI Performance Benchmarking

CommonProductProductivityAI Performance TestingBenchmarking

MLPerf Client is a newly developed benchmark created in collaboration with MLCommons, aimed at evaluating the performance of large language models (LLMs) and other AI workloads on personal computers (from laptops to desktops to workstations). This benchmark simulates real-world AI tasks to provide clear metrics on how systems handle generative AI workloads. The MLPerf Client working group hopes this benchmark will drive innovation and competition, ensuring that personal computers can meet the challenges of an AI-driven future.

Evaluate the performance of large language models and other AI workloads on personal computers
Provide clear performance metrics to help understand the system's capability to handle generative AI workloads
Drive innovation and competition in the AI space for personal computers
Support various hardware acceleration paths
including ONNX Runtime GenAI and Intel OpenVINO
Test using the Llama 2 7B large language model
covering a variety of tasks such as content generation
creative writing
and summarization
Clear system requirements

The target audience for MLPerf Client includes hardware manufacturers
software developers
and AI researchers. Hardware manufacturers can leverage this benchmark to showcase the AI performance of their products; software developers can use it to optimize their software and improve the performance of AI applications; AI researchers can utilize this benchmark to evaluate and compare the performance of different AI models.

Hardware manufacturers use the MLPerf Client benchmark to compare the performance of different GPUs on AI tasks.
Software developers utilize MLPerf Client to test the performance of their AI applications across various hardware configurations.
AI researchers employ MLPerf Client to assess the impact of different optimization techniques on model performance.

1. Visit the MLPerf Client GitHub release page and download the latest version of the benchmarking tool.
2. Ensure that the system meets the hardware and software requirements for benchmarking
including the installation of Microsoft Visual C++ Redistributable.
3. Extract the downloaded Zip file to a folder on your local drive.
4. Open the command line interface and navigate to the extracted folder.

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MLPerf Client Visit Over Time

Monthly Visits

36858

Bounce Rate

49.66%

Page per Visit

2.6

Visit Duration

00:01:14

MLPerf Client Visit Trend

MLPerf Client Visit Geography

MLPerf Client Traffic Sources

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