# Token Model W3.io introduces a next-generation token model that seamlessly integrates network revenue, staking incentives, and value creation towards long-term alignment. Unlike traditional token systems that rely on speculative demand, W3.io has designed a model where token ownership directly correlates with real world economic participation and transactions. By embedding programmable mechanics into value distribution, W3 ensures that partners, builders, and the community are rewarded proportionally to their contributions, sustaining a self-reinforcing growth cycle. * **Network Revenue maps to Token Ownership:** By incentivizing large amounts of the token supply to be locked up by participants doing jobs on behalf of the network we create a model where network revenue will flow to a large percentage of the token owners. * **Dual Incentivization of Rewards and Revenue:** We will use native token rewards to jumpstart involvement and reward early participation while at the same time building towards long term revenue flows using stablecoins. * **Significant Community Ownership:** We anticipate that 65-70% of the token supply will be distributed to network owners and their communities over time. Roughly 20-25% will be assigned on day 1, giving the community a very significant stake. * **Long Term Mindset:** We will require significant lockup commitments for staking as well as a slow release schedule for the initial distribution. * **Sell Disincentives & Redistribution:** If a partner or participant decides to sell their tokens during the initial holding time period, they forfeit the remainder of their initial stake, which is redistributed to long-term holders. This reinforces long-term holding behavior and rewards those who stay committed to the ecosystem. * **Sustained Price Growth Mechanics:** A combination of staking requirements, subnet expansion, and redistribution of forfeited stakes ensures continuous demand for W3 tokens while limiting sell-side pressure, supporting upward price movement at launch and beyond. --- # 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://learn.w3.io/network-model/token-model.md?ask= ``` 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.