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v2026.11,610 entries · CC-BY 4.0
Dictionary termTrack CStablev2026.2

MLCommons benchmark

A benchmark published by the MLCommons consortium for measuring AI system performance under standardised workloads, datasets, and submission rules, with the principal suites being MLPerf Training, MLPerf Inference, and MLPerf HPC.

ByCASRAI Editorial Board
· Last updated 21 May 2026

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Examples

Worked examples

  • Is an instance

    A vendor's MLPerf Inference v4.0 submission for a server-class GPU.

  • Is an instance

    A research group's open-division submission demonstrating a novel system architecture.

Counter-examples

Looks similar, but isn't

  • Not an instance

    A single-paper benchmark report not subject to peer-submission review.

  • Not an instance

    A leaderboard maintained on a personal blog.

Editorial commentary

MLCommons emphasises reproducible, audited performance numbers for hardware-software systems running canonical workloads. Submissions undergo peer review by other vendors. The benchmarks are widely cited in vendor marketing and procurement decisions, and have begun to expand into safety and trustworthy-AI evaluation.

References

  • Mattson et al., 'MLPerf Training Benchmark' (MLSys 2020); MLCommons technical reports.

Also known as

MLPerf

Machine-readable encodings

Use in your systems

JATS XML <role> element
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Schema.org DefinedTerm (JSON-LD)
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  "dateModified": "2026-05-21T02:22:51",
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Referenced across the research world

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