> For the complete documentation index, see [llms.txt](https://openvision-2.gitbook.io/whitepaper/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://openvision-2.gitbook.io/whitepaper/usdvision-token/deflationary-access-fees.md).

# Deflationary Access Fees

<figure><img src="/files/rHlzdK3kxIkFbYUsfHKc" alt=""><figcaption></figcaption></figure>

OpenVision integrates deflationary mechanics directly into platform usage to drive long-term
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token scarcity and alignment between utility and burn.

* **Burn Mechanics:** A portion of every paid API inference or training job is paid in
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  $VISION is burned automatically, reducing the circulating supply and anchoring value to
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  usage.
* **Dynamic Fee Multiplier:** The burn rate can be dynamically adjusted via DAO
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  governance based on network traffic, token supply, and ecosystem maturity.
* **USDC Surcharge Model:** Enterprises paying in USDC incur a premium unless
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  holding a required $VISION balance, encouraging on-chain participation, and
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  Reducing selling pressure.
* **Periodic Burn Proposals:** The DAO can propose and execute additional token burns
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  burns from protocol revenue or unused treasury allocations.

These mechanics ensure that as model adoption scales, so too does the deflationary
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pressure on $VISION, making it a self-reinforcing digital commodity tied to AI
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infrastructure demand.