ShareAI is a decentralized AI model network, where users can both earn and spend resources to access cutting-edge AI models. Instead of relying on a single provider, ShareAI ensures fair distribution of AI model access while compensating GPU owners who contribute computing power to the network.
How Users Can Consume AI Resources #
ShareAI provides two primary ways for users to consume AI models:
1️⃣ Tokens – Earned by sharing AI models with the network.
2️⃣ User Credits – Purchased credits that directly support GPU owners who power the decentralized AI network.
Why Do Consumption Strategies Matter? #
When a user sends an API request, ShareAI determines the best AI model based on availability, priority, and user preference. The system ensures:
✅ Optimal model selection – Prioritizing either tokens or credits based on user-defined strategies.
✅ Fair resource allocation – Rewarding users who contribute models while ensuring uninterrupted access to AI.
✅ Fallback mechanisms – Ensuring a model is always available, even if the user is low on tokens.
Understanding Consumption Strategies #
To optimize AI resource allocation, ShareAI supports two Main Strategies:
- Tokens First (
tokens_first) – Prioritizes tokens before using credits. - Credits First (
credits_first) – Prioritizes credits before using tokens.
Each Main Strategy has Substrategies that control how fallback behavior works across multiple AI models.
