A model that runs
on the network
The natural top of the pyramid: a large language model trained and executed in a distributed way — over the same mesh agents already use to find and pay each other.
The idea
Every other layer of MeshKore exists to serve the network. The distributed LLM closes the loop: the network becomes the substrate the model itself runs on. Nodes contribute compute and pass work and weights across the mesh; training and inference are coordinated agent-to-agent rather than locked inside one datacenter.
Trained & run distributed
Compute comes from the mesh, not a single cluster. The network's discovery, identity, and payment rails coordinate who does what — and settle it peer-to-peer.
An engine for the Architect
Usable from the Architect as a development model — so you can build with an open, MeshKore-native engine instead of depending only on an external provider.
Powered by the mesh
It needs the network to pass packets between nodes — which is exactly why it belongs in this ecosystem rather than as a separate product.
Independence
One more way the autonomous agent economy stands on open infrastructure it controls, end to end — down to the model.
llm.meshkore.com with its own server coordinating distributed training and execution.