The price of the model is not the bottleneck
Cost is settled after the model is chosen: by how the hardware is scheduled, by how many times the same context gets read again, and by a per-token price that ranks models in the wrong order. Three notes, all measured rather than quoted.
How far behind are open weights? Twenty months of a public model leaderboard, rebuilt from web archives and rescored on a single ruler. Six points behind at the top, with no trend. At the price anyone actually pays, an open-weight model strictly dominates 313 of the 398 models on sale. What running a model actually costs Three field notes on utilisation, on repetition inside an agent loop, and on why dollars per million tokens picks the wrong model. Same workload, same two 2017 cards, same bill: 27.55 tokens per second at one concurrent request, 435.62 at 128. Serving modern models on 2017 silicon Four experiments asking how far nine-year-old GPUs go against models released this year, run on a shared academic cluster. A 744B mixture-of-experts at one bit on eight V100s. 720p video, with audio, in five minutes on two of them.
Sampling and keyword search were workarounds for expensive reading
Annotation now costs little enough to read a population document by document. Once that is true, the two oldest design assumptions in empirical work, draw a sample and search for a keyword, stop being necessary.
Reading the whole population Four populations labelled in full rather than sampled, what full coverage costs on real hardware, and where that cost actually goes. 149,364 papers, 131.7 million job postings, 144,101 dissertations. Of the laboratory-automation papers the census accepts, 97% never call themselves that. Where CS graduates go US computing dissertations linked person by person to what their authors did next. The career panel does not know what anyone studied; the dissertations do. 144,101 dissertations from 2000 to 2025, 70,624 of them matched to a career profile.
The same cost question, in a different medium
What a real place costs to reconstruct from public data, to stream to an ordinary browser, and to generate from nothing.
The Illinois main quad, from lidar A 450 by 600 metre crop of the main quad as a gaussian splat you can fly around in the browser. Shape comes from a public airborne lidar survey, not from photographs of the site. 17.9 million gaussians, cut into 285 tiles and streamed by distance. Rebuilding a campus from public data How that model is built and streamed. Public lidar and public aerial photography only, no Street View, which is a design constraint rather than a disclaimer. Density came from cutting the scene into 20 pieces, not from the densification knob, which bought 37% finer spacing for 5× the gaussians. 167 MB ships. What a finished second of generated film costs A 43 second animated short, picture and sound generated together, made in a week of evenings on one desk machine. 8,779 seconds of compute for 41 seconds of picture on the pass where nothing went wrong. Rewriting one performance cost three quarters of that again.