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Token Value Mechanics

This document explains how Hokusai tokens derive and maintain their value within the ecosystem.

Value Sources​

1. Model Performance​

The primary value driver is the performance of AI models in the ecosystem:

Performance Metrics​

  • Hokusai models are uniquely focused on maximizing their performance against their defined performance benchmark. This is likely a touch myopic, but is designed for simplicity and clarity.

2. Usage Demand​

Token value is directly tied to model usage. As performant models generate more value, we anticipate that they will be used more frequently and/or the price of accessing the API will rise. This will then contribute to burning the supply:

Token Supply​

Token Supply = Base_Value * (1 + Mint_Rate) * (1 - Burn_Rate)

3. Supply Dynamics​

The token supply is managed through several mechanisms:

Supply Controls​

  1. Minting

    • Performance-based minting
    • Governance-controlled caps

  2. Burning

    • Usage-based burning
    • Governance actions

Price Discovery​

Bonding Curve​

The bonding curve provides continuous price discovery:

Price = Initial_Price * (1 + Rate)^Supply

Where:

  • Initial_Price = 0.01 USDC
  • Rate = 0.1% per token
  • Supply = Current token supply

Price Bounds​

  • Minimum: 0.001 USDC
  • Maximum: 10 USDC
  • Dynamic adjustment through governance

Value Metrics​

Key Indicators​

  1. Performance Metrics

    • Model improvement rate
    • DeltaOne issuance
    • Burn rate

  2. Market Metrics

    • Trading volume
    • Liquidity depth
    • Price stability

  3. Usage Metrics

    • API request volume
    • Active users
    • Enterprise adoption
    • Adoption by other AI models

Next Steps​

For additional support, contact our Support Team or join our Community Forum.

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