Meshcore proposes a peer-to-peer architecture that enables distributed large language model inference without centralized servers.

Meshcore introduces a decentralized network design for running LLM inference across connected nodes rather than relying on centralized cloud infrastructure

The P2P architecture aims to reduce latency, improve privacy, and distribute computational load across participating computers

This approach could democratize access to large language models by leveraging existing hardware in a mesh network topology