Data

This rung is about what a model is trained on and what that costs or constrains: how much usable text exists, whether synthetic data can stand in for it, who owns it, what licensing it costs, and how data quality changes what a model can do per token. It is the very start of the chain that ends in a task price — the input paid for before a single token is served.

Read this first: the rung holds three sources. It was first compiled on 2026-09-24 from one analysis piece (the Authors Guild's summary of Bartz v. Anthropic) and extended the same day with Reddit's 2024 IPO filing and Epoch AI's forecast of the public data stock. That gives it two prices for training data — one set in court, one negotiated — and one supply estimate. It is still not a picture of the training-data market: each price was set by essentially one buyer. No live market call rests on this rung.

What this rung prices

The numbers this rung owns — two prices, not yet one market:

• About $3,000 per book, a penalty: the minimum per-title payment from a $1.5 billion settlement over 7 million pirated book copies, covering roughly 500,000 titles (preliminary approval 25 September 2025) (Authors Guild summary). A ceiling on what a licence would cost, not a market rate.
• $203.0 million over two to three years, a licence: the aggregate value of the data deals Reddit signed in January 2024, at least $66.4 million of it recognised in 2024 — roughly $68–102 million a year across all contracts (this KB's arithmetic), from substantially one buyer (Reddit S-1). Dated February 2024 — never cite it as current.

See the price of training data.

The binding constraint, as far as three sources show it: who can be paid, not how much exists — yet. Free public text still has headroom: Epoch AI puts the effective stock at ~300 trillion tokens, fully used between 2026 and 2032 (central 2028), and ranks data behind power and chips as a limit on scaling to 2030 (Epoch AI). Meanwhile the paid side is shaped by provenance: the court attached money to how books were obtained, not to training on them (acquisition versus training). The supply date has already moved once by four years, so this reading is provisional. See the data stock.

How it reaches the token price, and where the chain breaks. A data cost is paid once and spread over every token a model serves. Turning either price into a cost per token needs two numbers this rung does not hold: how many tokens the purchased data amounts to, and how many served tokens the cost is spread across. The supply estimate adds a third link — when free data runs out, the next model's training bill rises (licensed data, or synthetic data at roughly twice the training compute) — but still no conversion.

Why it sits here and not next door. models would claim anything about what training produces; these sources say what the inputs cost and how much of them exists. inference-economics prices tokens at serving time; these are costs incurred before serving begins. Epoch's power and chip findings belong to energy and hardware; only its data section is compiled here.

The load-bearing findings

• ~$3,000 per title is a penalty ceiling, not a going rate — and the unit matters: the same $1.5bn is ~$214 per copy downloaded, a figure worked out only to show the sensitivity and not to be cited. The price of training data.
• A licence is priced per year of access, not per work. Reddit's $203.0M buys an API plus quarterly bulk transfers; its 2024 minimum alone was over four times all of Reddit's "other revenue" in 2023. The price of training data.
• The settlement priced acquisition, not training. Most coverage collapsed the two. Acquisition versus training.
• "We run out of data in 2026" is a misquote. Epoch's 2022 estimate said high-quality text would be used up before 2026; its 2024 estimate moved the window to 2026–2032, central 2028. The data stock.

Frontier — What's Moving Now

• The live licence price: Reddit's January 2024 contracts reach the end of their terms between January 2026 and January 2027, and its 2026 filings no longer break licensing out.
• The data window has opened (2026–2032); whether Epoch has moved it again is not in this KB.
• The final-approval outcome of the Bartz settlement is unresolved in this KB.
• See the open questions for the open questions and the checks behind them.

Concept Map

Concepts

Concept	Sources	Evidence	Last Updated
The Price of Training Data	2 (1 analysis, 1 technical report)	Moderate; each price from one buyer	2026-09-24
Acquisition Versus Training	1 (analysis)	Moderate to weak, single source	2026-09-24
The Data Stock and When It Runs Out	1 (technical report)	Moderate, single forecaster	2026-09-24

Entities

Entity	Type	Sources
Anthropic	Lab	1
The Authors Guild	Organization	1
Reddit	Company	1
Epoch AI	Organization	1

Timeline

See the timeline for chronological developments.

Sources

#	Title	Type	Date	Status
1	What Authors Need to Know About the Anthropic Settlement (Bartz v. Anthropic, $1.5bn class settlement)	analysis	2025-09-25	compiled
2	Reddit, Inc. — Form S-1 Registration Statement (data licensing arrangements, January 2024)	technical-report	2024-02-22	compiled
3	Can AI scaling continue through 2030? (Epoch AI)	technical-report	2024-08-20	compiled

Standing

Read it, for all three. Nothing on this rung was done first-hand. A piece built on it is a coverage piece unless it teaches one of the three distinctions the sources make clear: acquisition versus training, a licence versus a settlement, and what "running out of data" actually means.