> For the complete documentation index, see [llms.txt](https://cubic-2.gitbook.io/cubic-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://cubic-2.gitbook.io/cubic-docs/tokenomics/computational-power-model.md).

# Computational Power Model

CubiC introduces a **computational power (hashrate) model** to quantify user contribution and determine reward allocation.

#### Calculation Mechanism

* **Investment Contribution:**\
  Investment Amount × 1
* **Referral Contribution:**\
  Referral Reward × 2

#### Example

* A user investing **10,000 USDT** receives:\
  → 10,000 × 1 = **10,000 computational power**
* A user generating **100,000 USDT in referral rewards** receives:\
  → 100,000 × 2 = **200,000 computational power**

This model incentivizes both **direct participation and network growth**, reinforcing the dual structure of the ecosystem.