# AI Execution & Token Economy

#### $ART-Based Compute Metering

All model inference and content generation tasks are metered through the $ART token. Execution costs are dynamically calculated based on model type, input complexity, GPU runtime, and priority load. This ensures that compute resources are priced according to real usage and enables sustainable provisioning through decentralized compute backends or third-party execution layers.

#### Model Engagement-Driven Reward Mining

Every deployed model is eligible to accrue $ART through a usage-weighted incentive system. Reward distribution is calculated from multiple engagement vectors — including inference volume, remix propagation, and user feedback ratings — allowing developers to monetize their models without custodial intermediaries or licensing friction.

#### Curation-Informed Content Discovery

ArtisanAI’s discovery logic is governed by token-weighted curation signals. Actions such as likes, stars, forks, and citations are recorded on-chain and influence the visibility and ranking of content and models across the interface layer. This system ensures that high-value work is surfaced through a combination of economic backing and network consensus, not algorithmic opacity.

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