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pith:TTWPTCLF

pith:2025:TTWPTCLF73VTHWTHTU7DKTBP72
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Energy Scaling Laws for Diffusion Models: Quantifying Compute in Image Generation

Aniketh Iyengar, Boris Ruf, Jiaqi Han, Marcin Detyniecki, Stefano Ermon, Vincent Grari

An adapted Kaplan scaling law predicts GPU energy use for diffusion models from FLOPs.

arxiv:2511.17031 v2 · 2025-11-21 · cs.LG · cs.CV · cs.CY

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\pithnumber{TTWPTCLF73VTHWTHTU7DKTBP72}

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2 Internet Archive
3 Author claim open · sign in to claim
4 Citations open
5 Replications open
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Claims

C1strongest claim

Our energy scaling law achieves high predictive accuracy within individual architectures (R² > 0.9) and exhibits strong cross-architecture generalization, maintaining high rank correlations across models and enabling reliable energy estimation for unseen model–hardware combinations.

C2weakest assumption

denoising operations dominate energy consumption due to their repeated execution across multiple inference steps

C3one line summary

An adapted scaling law predicts GPU energy consumption for diffusion model inference with R² > 0.9 within architectures and strong cross-architecture generalization.

References

33 extracted · 33 resolved · 8 Pith anchors

[1] The Gentle Singularity 2025
[2] Wolff Anthony, Benjamin Kanding, and Raghavendra Selvan 2007
[3] de Araújo, JPW, and MinervaBooks 2024
[4] Measuring the environmental impact of delivering AI at google scale 2025
[5] Scaling Rectified Flow Transformers for High-Resolution Image Synthesis 2024 · arXiv:2403.03206

Formal links

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Receipt and verification
First computed 2026-05-18T03:10:11.796250Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

9cecf98965feeb33da679d3e354c2ffe82dcd5e5e297158998c01681294b0200

Aliases

arxiv: 2511.17031 · arxiv_version: 2511.17031v2 · doi: 10.48550/arxiv.2511.17031 · pith_short_12: TTWPTCLF73VT · pith_short_16: TTWPTCLF73VTHWTH · pith_short_8: TTWPTCLF
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/TTWPTCLF73VTHWTHTU7DKTBP72 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 9cecf98965feeb33da679d3e354c2ffe82dcd5e5e297158998c01681294b0200
Canonical record JSON
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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2025-11-21T08:12:47Z",
    "title_canon_sha256": "27cd6c96af1f6e27af6aacab836b4eb0447ee92fc058e070a7a2efd42f56eed7"
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