# Revenue Model

The network has varied revenue sources:

1. A portion of publishing and access fees paid by data contributors to publish in datanets.
2. Datanet lockup fees — datanets must lock 20k REPPO to spin up a datanet. Fifty percent remains locked while the datanet is live, and 50% goes to the network.<br>
3. Datanet emissions tax — datanet owners seed their datanet either with REPPO or their native token. If they seed in REPPO, there is no tax. If they seed in their native token, a 15% tax is collected and sent to the Foundation treasury.

Any REPPO bought on the market and seeded acts as direct revenue for REPPO holders. All tax revenue from emissions goes to the treasury, contributing to protocol operations and buybacks.

In V2, the majority of publishing fees and access fees go to the datanet owner, minus a small network fee deducted from the total fees accrued by the datanet each epoch.\
\
These fees can either be in USDC or the native token.

#### Performance Pool

Under the current staking and reward distribution spec, datanet staking rewards come from a **Performance Pool**.

The Performance Pool is funded by:

* **50% of datanet spin-up fees**
* **10% of all publishing fees**
* **10% of all data access fees**

Rewards are not paid from network emissions.

Instead, every third epoch, **5% of the Performance Pool** is distributed.

The current split is governance-adjustable:

* **80%** to REPPO stakers
* **20%** to datanet owners

New datanets are not eligible for Performance Pool rewards in their launch epoch.

They must complete one full epoch before earning from the pool.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://reppo-labs-xyz.gitbook.io/reppo-labs/economics/revenue-model.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
