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Dictionary termTrack CStablev2026.2

Compute (FLOPs estimate)

The total floating-point operations consumed by training a model, conventionally reported as a single number (e.g., 3.0 x 10^25 FLOPs) used as a regulatory and scientific proxy for training-run scale.

ByCASRAI Editorial Board
· Last updated 21 May 2026

Examples

Worked examples

  • Is an instance

    A model card declaring '~3.8 x 10^25 training FLOPs'.

  • Is an instance

    A regulator's classification of a model as systemic-risk based on the FLOPs estimate.

Counter-examples

Looks similar, but isn't

  • Not an instance

    Reporting only GPU-hours (related but hardware-coupled).

  • Not an instance

    Reporting energy consumption (related but not identical).

Editorial commentary

Training FLOPs are estimated from the standard 6 N D approximation for transformer training (6 times parameter count times tokens), with refinements for MoE and non-dense architectures. The metric appears in EU AI Act thresholds for systemic-risk classification (10^25 FLOPs) and US executive orders (10^26 FLOPs).

References

  • Hoffmann et al., 'Training Compute-Optimal Large Language Models' (NeurIPS 2022); EU AI Act Article 51 systemic-risk threshold.

Also known as

training FLOPs · training compute

Machine-readable encodings

Use in your systems

JATS XML <role> element
xml
<role vocab="credit"
      vocab-identifier="https://casrai.org/dictionary/"
      vocab-term="Compute (FLOPs estimate)"
      vocab-term-identifier="https://casrai.org/dictionary/term/compute-flops-estimate" />
Schema.org DefinedTerm (JSON-LD)
json
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  "identifier": "https://casrai.org/dictionary/term/compute-flops-estimate",
  "description": "The total floating-point operations consumed by training a model, conventionally reported as a single number (e.g., 3.0 x 10^25 FLOPs) used as a regulatory and scientific proxy for training-run scale.",
  "inDefinedTermSet": "https://casrai.org/dictionary/domain/ai-ml-research-outputs#set",
  "url": "https://casrai.org/dictionary/term/compute-flops-estimate",
  "sameAs": [
    "training FLOPs",
    "training compute"
  ],
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "publisher": {
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  },
  "dateModified": "2026-05-21T02:22:51",
  "inLanguage": "en"
}

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