MLPerf Client v2.0 Expands AI PC Benchmarking with Image Generation and Agentic AI
New benchmark categories for generative AI and agentic workflows arrive alongside updated LLM tests, as the industry
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SAN FRANCISCO, Aug. 18, 2026 (GLOBE NEWSWIRE) — MLCommons®, an open engineering consortium dedicated to improving machine learning performance and transparency, today announced the release of MLPerf® Client v2.0, the latest version of its industry-standard benchmark for evaluating AI performance on personal computers.
MLPerf Client measures how effectively PCs—from laptops and desktops to workstations—run AI workloads locally. With the release of v2.0, the benchmark now includes new Agentic AI and Image Generation capabilities alongside its established LLM benchmarking of real-world tasks like summarization, content creation, and code analysis, reporting metrics for both responsiveness and throughput.
New in MLPerf Client v2.0
Version 2.0 introduces a range of new features, refinements, and expanded support designed to keep pace with the rapid evolution of AI-enabled hardware and software:
Major Workload Changes
- New Image Generation Category: Adding this category significantly enhances the benchmark’s utility by enabling evaluation of generative visual capabilities. This category features Flux.2 klein 4B as an experimental test.
- New Agentic AI Category: Benchmarks agentic AI performance through Software Engineering (SWE) Agent and Data Analyst Agent scenarios. It reports end-to-end performance, including a breakdown of LLM inference and tool execution times.
- Updated LLM Inference tests: This release upgrades Phi 3.5 mini instruct in the required workloads to Phi 4 Mini Instruct, while introducing Qwen 3 8B as an experimental test. Base tasks now include an Intermediate Summarization task featuring an input prompt of roughly 4K tokens.
These updates mark another major step toward a comprehensive, cross-platform benchmark for client AI computing.
MLPerf Client is the product of a collaboration among technology leaders, including AMD, Intel, Microsoft, NVIDIA, Qualcomm Technologies, Inc., and top PC OEMs. These participants have contributed resources and expertise to the creation of this AI benchmark.
MLPerf Client v2.0 is freely available for download, and the source code is open for inspection and community contribution via the MLCommons GitHub repository. For downloads, documentation, and additional details, visit mlcommons.org.
GitHub releases (Windows, macOS, Linux): https://github.com/mlcommons/mlperf_client/releases
About MLCommons
MLCommons is an open engineering consortium with a mission to make machine learning better for everyone. The organization produces industry-leading benchmarks, datasets, and best practices that span the full range of ML applications—from massive cloud training to resource-constrained edge devices. Its MLPerf benchmark suite has become the de facto standard for evaluating AI performance.
Learn more at www.mlcommons.org.
Press Contact: press@mlcommons.org
