> For the complete documentation index, see [llms.txt](https://velocity-network.gitbook.io/velocity-network/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://velocity-network.gitbook.io/velocity-network/usdvlct-tokenomics/gas-fees.md).

# Gas Fees

### Design Principles

The network charges a fee for writing credential metadata to the ledger. This includes:

* **Participant registration** (writing institution's permissions to the chain)
* **Credential registration** (initial issuance anchor)
* **Credential revocation** (status updates)

These operations ensure that credentials remain discoverable, verifiable, and dynamically updatable over time. As such, they form a critical part of the network’s trust infrastructure.

Gas fees are designed as **low-cost, high-frequency infrastructure primitives**.

The pricing model is therefore optimized to:

* Ensure **frictionless issuance and revocation at scale**
* Prevent **cost barriers to maintaining credential accuracy**
* Preserve **predictability for enterprises and governments**
* Maintain **native alignment with the $VLCT token economy**

In particular, revocation must remain inexpensive. If revocation is costly, it is often avoided—undermining the reliability of the entire system.

### Token-Native Pricing Model

Unlike verification fees, credential write operations are **anchored in token units**, not fiat.

At the reference point:

* R<sub>0</sub>=0.10 USD
* **Base cost per operation**: F<sub>0</sub>=0.1 $VLCT

This corresponds to:

* **$0.01 per credential registration**
* **$0.01 per revocation**

### Price Evolution

As the token price increases, the fiat cost of credential writes grows sub-linearly using a dampening function:

C<sub>t</sub>=(F<sub>0</sub>⋅R<sub>t</sub>)⋅(R<sub>t</sub>/R<sub>0</sub>)<sup>α</sup>&#x20;

Where:

* α=0.1 (strong dampening)

Equivalently, token cost evolves as:

F<sub>t</sub>=F<sub>0</sub>⋅(R<sub>t</sub>/R<sub>0</sub>)<sup>α</sup>&#x20;

### Pricing Scenarios (α = 0.1)

| $VLCT Price | Multiple | Fiat Cost | Tokens Paid |
| ----------- | -------- | --------- | ----------- |
| $0.10       | 1×       | $0.01     | 0.10        |
| $0.20       | 2×       | $0.011    | 0.11        |
| $0.50       | 5×       | $0.013    | 0.12        |
| $1.00       | 10×      | $0.016    | 0.13        |
| $2.00       | 20×      | $0.019    | 0.15        |
| $5.00       | 50×      | $0.024    | 0.18        |
| $10.00      | 100×     | $0.032    | 0.20        |
| $20.00      | 200×     | $0.043    | 0.22        |
| $50.00      | 500×     | $0.068    | 0.27        |
| $100.00     | 1000×    | $0.100    | 0.32        |

### Economic Implications

#### 1. Extremely Low and Stable Fiat Costs

Even under a **1000× increase in token price**, the cost of writing a credential grows only from:

* **$0.01 → \~$0.10**

This ensures the network remains viable for:

* large-scale issuance (millions of credentials)
* frequent updates and revocations
* public sector and enterprise adoption

#### 2. Gradual Increase in Token-Denominated Cost

Unlike verification, token cost does not collapse — it **grows slowly over time**.

* 0.10 → 0.32 tokens

This ensures:

* continued token demand
* meaningful economic participation
* alignment with network growth

#### 3. Decoupling Infrastructure from Speculation

The model ensures that core infrastructure operations are **not exposed to token volatility**.

* Fiat costs remain predictable
* Token costs adjust gradually
* No sudden pricing shocks

### Positioning Within the Network Economy

Credential writes are intentionally priced as:

> **“low-cost trust maintenance operations”**

They are not designed to maximize value capture, but to ensure:

* continuous data integrity
* accurate credential lifecycle management
* scalable network growth

Economic value is instead concentrated in:

* verification events
* staking demand
* network usage at scale

### Bottom Line

This model creates a system where:

* writing and updating credentials remains **cheap, predictable, and scalable**
* token demand grows **gradually and sustainably**
* and the network can support **global, high-frequency credential activity** without friction