A model that spends more time thinking at inference before it answers. Chapter 2.
From The AI Compute Race. Read the book
Where the book uses it
- Chapter 2 — The Discovery That Changed Everything
How a formula about compute and capability became a bill: the scaling laws, the first supercomputers built to test them, and why the money came before the paper.
Sources that use it
- Ben Cottier, Ben Snodin, David Owen and Tom Adamczewski, “LLM inference prices have fallen rapidly but unequally across tasks,” Epoch AI Data Insight, 12 March 2025 (from the page’s method block, read 19 September 2026: “Across all of these benchmarks and performance thresholds, we found prices declining between 9x per year and 900x per year, with a median of 50x per year”, on six benchmarks with a rate fitted at each score threshold that a new model had set; “The fastest price drops in that range have occurred in the past year, so it’s less clear that those will persist”; “We set a threshold of at least 4 data points to include a regression result”; “All prices were a 3:1 weighted average of input and output token prices”; “We excluded reasoning models from our analysis of per-token prices. Reasoning models tend to generate a much larger number of tokens than other models, making these models cost more in total to evaluate on a benchmark”; with all model data before January 2024 removed, “the median rate increased from 50x per year to 200x per year”; the release dates in the page’s table of priced models run from 20 November 2021 to 5 February 2025, and the data files behind the page are stamped as updated on 20 November 2025; the method block re-read live on 21 September 2026, every passage above unchanged, archived as VERIFY 260921/R68 B). In the Sources
Related terms
From the glossary of The AI Compute Race.
How to cite this page
Dryburgh, Lee S. “Reasoning model.” In The AI Compute Race. DRYBURGH. https://dryburgh.com/vol1/glossary/reasoning-model (accessed 2026-11-01).
BibTeX
@misc{dryburgh-reasoning-model-2026,
author = {Dryburgh, Lee S.},
title = {{Reasoning model}},
howpublished = {In \emph{The AI Compute Race}, DRYBURGH},
year = {2026},
url = {https://dryburgh.com/vol1/glossary/reasoning-model},
note = {Accessed 2026-11-01}
}