# FreeAI Model

## Overview

Aggre's FreeAI aims to offset the cost of user subscriptions with AG token rewards, making access to the best AI models effectively free. This model balances user incentives with platform revenues and expenses, ensuring financial viability.

## How it Works

<figure><img src="/files/MEJ129ZhZbeu3gD2u0TI" alt="" width="450"><figcaption><p>New AG tokens are minted in parallel with growing Aggre revenues</p></figcaption></figure>

### Inputs

#### 1. Paid Subscriptions:

* Users subscribe to Aggre, paying a monthly fee to access AI credits from the top AI models.
* Different subscription tiers offer varying quantities of AI credits, determining the number of prompts users can submit.

#### 2. User Data Contributions:

* Users actively submit prompts and rate the performance of AI models.
* These activities generate valuable data that can be packaged and sold as data points.

#### 3. Advertisements:

* In-app advertisements displayed to free-tier users.

### Outputs

#### 1. Operational Costs:

* Routing user prompts through top AI models via API calls.
* Infrastructure and other operational expenses

#### 2. AG Token Rewards:

* Users earn AG token by rating AI model performance, with dynamic emissions based on current token price and the user's subscription tier.

## Achieving Economic Balance

#### Subscription Revenue vs. AI Credit Costs:

* Subscription fees are set higher than the cost of the corresponding AI credits. This ensures that each subscription generates a positive cash flow for the platform.&#x20;
* For example, if a subscription costs $20 per month, the cost of the AI credits provided should be slightly less, ensuring a margin that contributes to overall revenue.

#### Balancing AG Rewards with Sustainability:

* The platform limits the number of prompts a user can submit per month based on their subscription tier, ensuring that AG token emissions are controlled. Once users reach their maximum prompt limit, they can reload their credits, generating additional revenue for the platform.
* It is OK for Aggre to run at a -PNL when considering the value of AG token rewards distributed while in a growth oriented trajectory. For example, OpenAI runs at a -$14/month loss per user. Intelligent tokenomics and real yield can offset AG token rewards.


---

# 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://docs.aggregated.app/overview/ag-token/freeai-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.
