# AI training data pricing models

URL: https://sellmydatatoai.net/guides/ai-training-data-pricing-models
Reviewed: 2026-11-08

AI training data is priced in five main ways: a flat license fee, a price per unit such as per minute of video or per task, a recurring subscription, a revenue share or staged milestone payments. Exclusivity is the biggest multiplier, with AIData.Broker putting exclusive deals at about 2.5 to 5 times non-exclusive ones. Rights clarity and uniqueness drive the rest.

## Key takeaways

- Flat fees suit one-off company archives, unit pricing suits media and tasks, and subscriptions suit data that is refreshed.
- AIData.Broker reports a median of $280,000 in buyers' published offers per company, against a median of $31,600 in sales made public.
- Exclusive deals cost about 2.5 to 5 times non-exclusive ones, according to AIData.Broker.
- Research licenses are cheapest but usually do not permit training a production model, according to Phyllo.

There is no list price for AI training data. Each deal is priced on the dataset, the rights granted and the buyer's alternatives. What is consistent is the set of structures used to express a price, and the factors that move it up or down.

## How is AI training data priced?

AI training data is priced using five structures, and many deals combine two of them. The right structure depends on whether the data is a one-off archive, a stream of new records or a catalog sold to many buyers.

| Model | How it works | Published example | Suits |
| --- | --- | --- | --- |
| Flat license fee | One price for a defined dataset and set of rights | Polyshares: four published deals of $110,000 to $450,000, all perpetual and exclusive (ddiy.co) | One-off company archives |
| Per unit | A unit price multiplied by volume | Adobe: about $3 per minute of video (Bloomberg, April 2024) | Video, audio, images and tasks |
| Subscription | An annual fee for ongoing access and updates | Reddit and Google: about $60 million a year (Reuters, February 2024) | Data that is refreshed |
| Revenue share | The seller receives a share of each resale | Troveo: paid from revenue share, no fees (ddiy.co) | Catalogs sold many times |
| Milestone payments | Payment in tranches as delivery and acceptance are met | Handshake AI: milestone payments (ddiy.co) | Large or staged deliveries |

Hybrids are common. ddiy.co's October 2026 compilation lists Labelbox Prism as paying an upfront fee plus a revenue share, and many flat-fee deals are paid in stages tied to acceptance.

## What units are used in per-unit pricing?

Per-unit pricing uses the unit the buyer actually consumes. AIData.Broker, as quoted by ddiy.co, lists the company, the code repository, the hour of audio or video and the task as the usual units, each multiplied by volume.

| Data type | Typical unit | Reported figure |
| --- | --- | --- |
| Video footage | Per minute or per hour | About $3 per minute (Bloomberg on Adobe, April 2024) |
| Video for OpenAI | Per minute | $1 to $4 per minute, according to a February 2026 Versos post that cites no source |
| Company records | Per company | Median of $280,000 in buyers' published offers (AIData.Broker via ddiy.co) |
| Source code | Per repository | About $25,000 for a shut-down startup's codebase (MIT Technology Review, October 2026) |
| Agent tasks | Per task or per taskset | Rates set per listing on DataVendor, not published as a range |

Buyers usually price a company archive as a whole rather than per document, according to ddiy.co. That is why ranges for company data are quoted per company.

## What do published price ranges look like?

Published price ranges for AI training data run from a few thousand dollars for research use to over a million dollars for exclusive or custom data. Phyllo's September 2026 guide gives reported market bands, which it says should be treated as ranges rather than quotes.

| License type | Reported range | Coverage |
| --- | --- | --- |
| Research | $5,000 to $15,000 | Academic and non-commercial use |
| Commercial | $25,000 to $500,000 and above | Commercial training and deployment |
| Professional annual | $25,000 to $50,000 a year | Ongoing access with periodic updates |
| Enterprise annual | $50,000 to $500,000 a year | Real-time access and custom features |
| Exclusive or custom | $1 million and above | Bespoke collection, exclusive rights, custom benchmarks |

For company data, buyers publish their own ranges. Mercor's listing, as compiled by ddiy.co in October 2026, puts law firms at $50,000 to $1.2 million, construction companies at $115,000 to $1 million and call centers at $20,000 to $250,000 per company. These are offer ranges, not completed prices.

Completed prices tend to sit lower. AIData.Broker reports a median of $280,000 across buyers' published offers but a median of $31,600 across the few sales made public. Fortune reported in September 2026 that payments are typically $10,000 to $100,000 per company, citing SimpleClosure, while Google bid $10 million for bankrupt Spirit Airlines' data archive in an August 2026 auction that was subject to court approval when reported.

Our [AI data deals tracker](https://sellmydatatoai.net/ai-data-deals) lists reported transactions, and [how much is your data worth to AI companies](https://sellmydatatoai.net/guides/how-much-is-your-data-worth-to-ai) explains the same numbers from the seller's side.

## What makes one dataset worth more than another?

One dataset is worth more than another when it is harder to replace and safer to use. Volume matters less than most sellers expect.

- Exclusivity: AIData.Broker puts exclusive deals at about 2.5 to 5 times non-exclusive ones.
- Rights clarity: a smaller dataset with clear provenance can be worth more than a larger one whose best parts must be excluded, according to Nixon Peabody.
- Human authorship: DataVendor reports that labs pay more for code written mostly by people, and for complex products.
- Language and difficulty: DataVendor names systems languages such as Rust, Go, C and C++ as attracting a premium.
- Context: production code with pull requests, issue tickets, runbooks and incident notes explains why code changed, which DataVendor says buyers value.
- Reproducibility: DataVendor notes that evaluation sets command more attention when independent reviewers can reproduce the scores.

License scope moves price as well. A license limited to one model, one field of use or a fixed term should cost less than a perpetual license covering every model your company builds.

## How does exclusivity change the price?

Exclusivity raises the price because the seller gives up every other sale of the same data. AIData.Broker's estimate of 2.5 to 5 times a non-exclusive deal reflects that lost income.

You can narrow exclusivity to pay less for it. Common options are a time-limited exclusive, an exclusive within one field such as legal drafting, or an exclusive against named competitors only. Polyshares, by contrast, makes exclusive and perpetual the default in its published deals, according to ddiy.co. Our guide to [exclusive vs non-exclusive data licenses](https://sellmydatatoai.net/guides/exclusive-vs-non-exclusive-data-licenses) covers the trade-offs.

## How should a buyer structure payment?

A buyer should structure payment so that money follows evidence. Pay a first installment on signing, the main payment on acceptance of the delivered data and, for larger deals, hold back a portion until the warranty period ends.

Published seller timelines show what the market expects. ddiy.co's compilation reports that Mercor pays 2 to 4 weeks after signing, micro1 takes up to 30 days to approve and pays 30 days after invoice, and Polyshares pays on net 30 to 60 day terms. Matching your schedule to these norms makes an offer easier to accept.

> **Check the permitted use before the price** Phyllo warns that research licenses usually do not permit training a production model. A cheap license that does not cover your use is the most expensive option once you have to re-license or retrain.

## Which pricing model should you choose?

The pricing model you choose should follow how the data will be used and how often it changes.

| Situation | Model that usually fits |
| --- | --- |
| One company's historical archive | Flat fee, paid in stages against acceptance |
| Media you will buy more of over time | Per unit with a volume tier |
| Data that is refreshed monthly or quarterly | Annual subscription |
| A seller who wants to keep upside | Lower upfront fee plus revenue share |
| A custom collection or evaluation set | Milestone payments tied to delivery batches |

## What does Sell My Data To AI charge buyers?

Sell My Data To AI charges buyers nothing to submit a requirement or review a shortlist. Any fee is agreed in writing before an introduction, and our [fees page](https://sellmydatatoai.net/fees) explains how this works. You negotiate the price and payment terms directly with the seller.

To get a view of what a dataset should cost before you negotiate, [book a buyer consultation](https://sellmydatatoai.net/book-a-consultation?side=buyer) or [submit a data requirement](https://sellmydatatoai.net/request-data).

## Frequently asked questions

### What is the cheapest way to buy AI training data?

The cheapest way to buy AI training data is a non-exclusive license to an existing dataset, ideally one already prepared for sale. Research licenses cost less again, with Phyllo reporting $5,000 to $15,000, but they usually do not permit training a production model. Cheap data that you later have to re-license or retrain without costs more in the end.

### Why are published offers so much higher than completed sales?

Published offers are ceilings set by buyers to attract sellers, while completed sales reflect what a specific dataset was worth after diligence. AIData.Broker reports a $280,000 median for buyers' published offers against $31,600 for the sales made public. Exclusions for personal data, client confidentiality and third-party content often reduce what is left to sell.

### Is revenue share a good deal for a buyer?

Revenue share suits a buyer that resells data, such as a platform or aggregator, because payment tracks income. For an AI lab training its own models, a revenue share is harder to calculate and audit, so a flat fee or subscription is usually simpler. Labelbox Prism combines an upfront fee with a revenue share, according to ddiy.co.

### Should I pay per token for text data?

Per-token pricing is rare for licensed company data, because buyers usually price an archive as a whole, according to ddiy.co. Tokens are useful for comparing offers and estimating training value, so ask sellers for token counts in the manifest. The Commission's EU AI Act template also asks providers to report text training data size in token ranges.

## Sources

- [How much is company data worth to AI?](https://ddiy.co/how-much-is-company-data-worth-to-ai/), ddiy.co, accessed November 2026
- [Sell company data to AI](https://ddiy.co/sell-company-data-to-ai/), ddiy.co, accessed November 2026
- [Best public data providers for AI training and grounding](https://www.getphyllo.com/post/best-public-data-providers-ai-training-grounding), Phyllo, accessed November 2026
- [Adobe is buying videos for $3 per minute to build AI model](https://www.bloomberg.com/news/articles/2024-04-10/adobe-is-buying-video-clips-for-3-per-minute-to-build-ai-model), Bloomberg, accessed November 2026
- [Exclusive: Reddit in AI content licensing deal with Google, sources say](https://tech.yahoo.com/ai/articles/exclusive-reddit-ai-content-licensing-041012503.html), Reuters (syndicated by Yahoo), accessed November 2026
- [Sell video content as AI training data](https://www.versos.ai/blog/sell-video-content-ai-training-data), Versos, accessed November 2026
- [AI labs are buying data from dead startups to train models](https://www.technologyreview.com/2026/10/13/1145755/ai-labs-buying-data-from-dead-startups-to-train-models), MIT Technology Review, accessed November 2026
- [micro1 tries to beat Google's bid to buy bankrupt Spirit Airlines' data](https://fortune.com/2026/09/14/micro1-tries-to-beat-googles-bid-to-buy-bankrupt-spirit-airlines-data-for-12-5-million-highlighting-value-of-data-to-ai-companies/), Fortune, accessed November 2026
- [AI training data marketplaces](https://datavendor.ai/blog/ai-training-data-marketplaces), DataVendor, accessed November 2026
- [Shopping for AI training data? Five diligence questions before you buy](https://www.nixonpeabody.com/insights/alerts/2026/10/26/shopping-for-ai-training-data-five-diligence-questions-before-you-buy), Nixon Peabody LLP, accessed November 2026
- [Explanatory notice and template for the public summary of training content for general-purpose AI models](https://digital-strategy.ec.europa.eu/en/library/explanatory-notice-and-template-public-summary-training-content-general-purpose-ai-models), European Commission, Shaping Europe's digital future, accessed November 2026

---

Book a free consultation: https://sellmydatatoai.net/book-a-consultation