Indicators / series
epoch.openai.rd_compute_usd.fy
Source: Epoch AI data hub — AI companies (Epoch AI) · CC BY 4.0 · CSV
Epoch AI, 'Data on AI Companies' (CC BY 4.0), epoch.ai/data
| id | value | grade | as of date | published date | tier | audited vs reported | extraction method | review status | retrieved at | http status | content hash | supersedes id | url | flags |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 6f9fe86ba4f354d8 | $4.0B | grade C, evidence tier 5 | 2024-12-31 | 2024-10-09 | 5 | estimated | api | approved | 2026-09-11 10:55 | 200 | 9b2f4ca0bcc7 | — | source page | |
| e22f46963466ac04 | $8.3B | grade C, evidence tier 5 | 2025-12-31 | 2026-02-20 | 5 | estimated | api | approved | 2026-09-11 10:55 | 200 | 9b2f4ca0bcc7 | — | source page |
Raw snippets and dispute text
- 6f9fe86ba4f354d8 {"Amount": "4000000000", "Category": "R&D cloud compute", "Company": "OpenAI", "Confidence": "Likely", "Date": "2024-12-31", "Id": "OpenAI 2024 R&D compute", "Notes": "Importantly, this may actually be ~$5-6B in incurred R&D compute expenses in 2024.\n\nThe article shows a graph with $3B in training expenses, and $1 in research compute amortization\n\nI'll take the amortization at face value here, but the actual spending on research compute in 2024 is then equal to 1B multiplied by the amortization schedule in years, which is described as multiple years. So $2B if amortized over two years, $3B if three years.\n\nThis is from a projection of 2024 spending published in October 2024, so numbers are not certain.", "Period type": "Year", "R&D compute spend": "4000000000.0", "Report date": "2024-10-09", "Source 1": "https://www.theinformation.com/articles/openai-projections-imply-losses-tripling-to-14-billion-in-2026?rc=9mzoog", "Source Type": "Media report"}
- e22f46963466ac04 {"Amount": "8300000000", "Category": "R&D cloud compute", "Company": "OpenAI", "Confidence": "Likely", "Date": "2025-12-31", "Id": "OpenAI 2025 R&D compute", "Notes": "\"Last year, OpenAI spent $8.3 billion [to train its models], about a billion less than it expected from its summer forecast.\"\n\nThis likely means all R&D spending, not just final training runs.", "Period type": "Year", "R&D compute spend": "8300000000.0", "Report date": "2026-02-20", "Source 1": "https://www.theinformation.com/articles/openai-boost-revenue-forecasts-predicts-112-billion-cash-burn-2030?rc=9mzoog", "Source Type": "Media report"}