A Decentralized Network for Large Language Model Inference
Executive Summary
LLMule is a groundbreaking peer-to-peer network that democratizes access to artificial intelligence by enabling users to share and monetize their local LLM computing resources. The platform creates a decentralized marketplace where users can either provide computing power to run AI models or consume AI services using the network's native token system.
Core Components
Network Architecture
- P2P Infrastructure: Decentralized network of nodes running local LLMs
- OpenAI-Compatible API: Standardized interface for seamless integration
- Smart Contract Layer: Built on Polygon for efficient token management
- Client-Server Architecture: Optimized for distributed computing
Tokenomics
Token Utility
- Consumer Usage: Users spend tokens for LLM inference
- Provider Rewards: Node operators earn tokens for computing
- Network Fee: Small percentage retained for platform sustainability
Token Distribution
- Free Tier: Limited tokens for new users to experience the network
- Price Parity: Initial token value pegged to OpenAI's per-million-token pricing
- Provider Economics: Competitive rewards to incentivize node operation
Stage One Implementation
User Onboarding