Compute in the 2020 report
Evidence you can use
Compute in the 2020 report
Historical snapshot: October 2020. Dates and populations are specified per row.
| Measure | Reported value | Definition and source |
|---|---|---|
| Estimated GPT-3 training cost | Approximately $10M | Expert estimate cited in the report, not disclosed actual cost.2020 report, PDF page 17 |
| ImageNet compute-efficiency trend | Halving every 16 months | Compute needed to reach a fixed performance level since 2012.2020 report, PDF page 22 |
The two figures describe different quantities: a model-specific cost estimate and a historical fixed-performance efficiency trend. Neither should be extrapolated as a universal rule or used as a current price.
Sources and dates
Historical snapshot published October 1, 2020. This web edition was prepared on 2026-10-11 from the online deck and original launch posts. Findings and forecasts retain their original time frame.
- 2020 report, PDF page 17Original 2020 report. This edition has no printed slide numbers. References use one-based PDF pages.
- 2020 report, PDF page 22Original 2020 report. This edition has no printed slide numbers. References use one-based PDF pages.
- State of AI Report 2020: online slides
- Nathan Benaich’s launch essayOctober 1, 2020.
Cite this page
Benaich, Nathan, and Ian Hogarth. “Compute in the 2020 report.” State of AI Report 2020. Historical report snapshot; web edition prepared 2026-10-11.