---
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title: >-
  20 days of compute vs 7 hours: rethinking what state-of-the-art means —
  Bertrand Charpentier, Pruna
description: >-
  Ranking image generation models the way Design Arena does it — 26,000 battles,
  62 seconds per generation — takes 20 days of compute, costs $5,000, and
  consumes roughly 400 marathons worth of energy. Bertrand Charpentier,
  cofounder and chief scientist at Pruna AI, uses that number to make a point:
  the same evaluation on a fast compressed model takes 7 hours and $265.
  Efficiency is a dimension of state of the art, not a footnote. The rest of the
  talk dismantles the idea that any single model holds the title. Leaderboard
  rankings disagree with each other — the same model goes from rank 10 on one to
  rank 5 on another. Most models lose 40% of their head-to-head battles, which
  means the top-ranked model is the wrong choice for nearly half of real use
  cases. His answer is the Pareto front: plot quality against latency or cost,
  find the frontier, and expect three or four models clustered tightly in
  quality score but varying up to 20x in efficiency. Evaluating this way tends
  to surface small specialized models rather than large foundation models.
  Speaker info: - https://www.linkedin.com/in/bertrand-charpentier-76995ab6/ -
  https://github.com/sharpenb --- Watch along with the corrected transcript,
  summary, timestamps and resources on this talk's official AIE page:
  https://ai.engineer/talks/hqHC6Z_lXyo-20-days-of-compute-vs-7-hours-rethinking-what-state-of-the-art-means-bertrand-charpentier-pruna
  Join our upcoming AI Engineer conferences (see https://ai.engineer landing
  page): - AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs
  and engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference
  returns - AIEi Sydney, December 7–8 — the first AIEi run alongside NeurIPS
  2026 in Sydney ---
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# 20 days of compute vs 7 hours: rethinking what state-of-the-art means — Bertrand Charpentier, Pruna

Ranking image generation models the way Design Arena does it — 26,000 battles, 62 seconds per generation — takes 20 days of compute, costs $5,000, and consumes roughly 400 marathons worth of energy. Bertrand Charpentier, cofounder and chief scientist at Pruna AI, uses that number to make a point: the same evaluation on a fast compressed model takes 7 hours and $265. Efficiency is a dimension of state of the art, not a footnote. The rest of the talk dismantles the idea that any single model holds the title. Leaderboard rankings disagree with each other — the same model goes from rank 10 on one to rank 5 on another. Most models lose 40% of their head-to-head battles, which means the top-ranked model is the wrong choice for nearly half of real use cases. His answer is the Pareto front: plot quality against latency or cost, find the frontier, and expect three or four models clustered tightly in quality score but varying up to 20x in efficiency. Evaluating this way tends to surface small specialized models rather than large foundation models. Speaker info: - https://www.linkedin.com/in/bertrand-charpentier-76995ab6/ - https://github.com/sharpenb --- Watch along with the corrected transcript, summary, timestamps and resources on this talk's official AIE page: https://ai.engineer/talks/hqHC6Z_lXyo-20-days-of-compute-vs-7-hours-rethinking-what-state-of-the-art-means-bertrand-charpentier-pruna Join our upcoming AI Engineer conferences (see https://ai.engineer landing page): - AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs and engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference returns - AIEi Sydney, December 7–8 — the first AIEi run alongside NeurIPS 2026 in Sydney ---

Canonical: https://liquidgold.cc/channel/aidotengineer/explore/video/20-days-of-compute-vs-7-hours-rethinking-what-state-749de1a184f5 · Channel: [AI Engineer](https://liquidgold.cc/channel/aidotengineer.md)

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