Epoch AI is a 501(c)(3) research nonprofit that maintains open datasets on AI models, compute, data centers, chips, and companies, runs its own benchmarks, and publishes research, a newsletter, and a podcast, all under a transparency policy that itemizes its funders and paid consultations. Facts below verified as of 2026-09-24.
Where the other sites in this category tell you what is winning this week, Epoch tells you how fast the whole field is moving, and lets you download the series behind the claim.
What it is #
A research organization, roughly 50 people, whose public products are data explorers (AI Models with 3,200+ entries from 1950 to today, AI Data Centers, Chip owners, Companies, Polling), benchmarks (the Epoch Capabilities Index, FrontierMath, MirrorCode, EBR-bench), papers and reports, short Data Insights, the Gradient Updates newsletter, and the Epoch After Hours podcast. Data is free to use with attribution under Creative Commons (CC BY), and a Python client library and data repositories live on its GitHub org. Its numbers are the citation of record for AI trend claims, used by Our World in Data, government AI-safety reports, and the financial press.
Status #
Actively maintained at near-daily granularity: the data page was stamped “Updated Sep. 24, 2026”, the day of verification, and its GitHub repositories show pushes the same day. HN traction is substantial and recurring: the FrontierMath launch drew 185 points in 2024, “FrontierMath was funded by OpenAI” drew 483 points in January 2025, and “Epoch confirms GPT5.4 Pro solved a frontier math open problem” drew 480 points in March 2026. Founded by Jaime Sevilla and collaborators; funding is donations (Coefficient Giving grants of $8.5M in 2025, $4.13M in 2024, and more, plus the Survival and Flourishing Fund, Jaan Tallinn, and Schmidt Sciences), with paid consultations disclosed on the transparency page.
Strengths #
- The most checkable actor in the category: funders, grants, and paid consultations (OpenAI, Google DeepMind, the EU AI Office) are named on one page.
- CC BY data plus a Python client means their series can go straight into your own analysis instead of a screenshot.
- Coverage spans hardware, data centers, and companies, not just model leaderboards, which is where the multi-year questions live.
Cautions #
- The FrontierMath funding controversy is the load test it had to pass: TechCrunch reported in January 2025 that Epoch “didn’t disclose that it had received funding from OpenAI” while developing a benchmark OpenAI’s models were scored on.
- Its response was structural (full disclosure plus a 2026 FrontierMath data audit), but the structural tension remains: the labs it benchmarks are also its consulting clients and neighbors in the funding ecosystem.
- Trend series are backward-looking; nothing here tells you which provider to buy this week.
Pricing #
Free: a donation-funded nonprofit whose data is CC BY licensed. It sells consultations and custom research to organizations, with no public price list. No reader-facing price is stated, so no price history applies.
Compared to #
- Artificial Analysis: live model-versus-model comparisons; Epoch answers the multi-year questions those snapshots sit inside.
- AI Release Tracker: the raw release stream; Epoch’s model dataset is the curated, parameterized version of the same history.
- Stanford HAI’s AI Index: a single annual curated report; Epoch is continuous and downloadable.
Bottom line #
Recommended for anyone who needs to cite how fast AI capability, compute, or cost is moving, with the data behind the number, not for weekly model selection. My disagreeable claim: the FrontierMath episode made Epoch more trustworthy, not less, because it is the only member of this category that responded to a conflict-of-interest scandal by publishing an itemized funder and client list, and none of its commercial peers has matched that.
Changes #
- 2026-09-24 - Created.
See also #
- Artificial Analysis - the present-tense measurement layer above Epoch’s trend lines
- AI Release Tracker - the raw release stream behind the model dataset
- LMArena - preference-based ranking, the opposite timescale of an Epoch series
- Trackers and Leaderboards Feature Matrix - the category comparison this note joins
References #
https://epoch.ai/ - homepage: tagline, 3,200+ model dataset, product map, update stamps (fetched 200, 2026-09-24)
https://techcrunch.com/2025/01/19/ai-benchmarking-organization-criticized-for-waiting-to-disclose-funding-from-openai/ - the funding-disclosure controversy (fetched 200, 2026-09-24)
https://github.com/epoch-research - active data and benchmark repositories, pushes on 2026-09-24 (fetched 200, 2026-09-24)
https://epochai.substack.com/ - the Gradient Updates newsletter (fetched 200, 2026-09-24)