# Referral Reward  (ETH)

This referral system operates on 6 levels, with level 1 being the highest and level 6 being the lowest. Via this program, **8% of the transaction tax is allocated to referral rewards in ETH**, 6% of which are then distributed among referrers and the users they refer. The remaining 2% tax is immediately rebated to the wallet that made the transaction.

You can start by generating your referral link and inviting more friends to join. Your network will expand as your downlines recruit more people, creating a multi-level structure.

To illustrate the distribution process, let's consider Alice who purchased $MMLM and managed to build a referral network that spreads across all 6 levels. Her referral rewards are as follows:

* 2% from her level 1 referees (those she directly refers).
* 1.5% from level 2.
* 1% from level 3.
* 0.75% from level 4.
* 0.5% from level 5.
* 0.25% from level 6.
* Alice also gets a 2% rebate on every $MMLM trade she makes.

<figure><img src="/files/g3ZwvmFp1sx1A9N7T2QF" alt="" width="290"><figcaption><p>MMLM Referral System</p></figcaption></figure>

From the perspective of Bob, a level 6 referee in Alice’s network, his 8% tax will be distributed as follows:

* 2% will directly be rebated to Bob’s wallet, serving as an incentive for newcomers to join and purchase $MMLM, while making it more rewarding for Bob to create is own network.
* 2% will be distributed to the level 6 upline holder, rewarding the direct referrer of Bob.
* 1.5% will be distributed to level 5.
* 1% will be distributed to level 4.
* 0.75% will be distributed to level 3.
* 0.5% will be distributed to level 2.
* 0.25% will be distributed to level 1, which is Alice.


---

# 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://mmlm.gitbook.io/mmlm/mmlm-reward-model/referral-reward-eth.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.
