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+title = "Distribution"
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+url = "/features/distribution/"
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+
+LocalAI supports distributing inference workloads across multiple machines. There are two approaches, each suited to different use cases:
+
+## Distributed Mode (PostgreSQL + NATS)
+
+Production-grade horizontal scaling with centralized management. Frontends are stateless LocalAI instances behind a load balancer; workers self-register and receive backends dynamically via NATS. State lives in PostgreSQL.
+
+**Best for:** production deployments, Kubernetes, managed infrastructure.
+
+[Read more]({{% relref "features/distributed-mode" %}})
+
+## P2P / Federated Inference
+
+Peer-to-peer networking via libp2p. Share a token to form a cluster with automatic discovery — no central server required. Supports federated load balancing and worker-mode weight sharding.
+
+**Best for:** ad-hoc clusters, community sharing, quick experimentation.
+
+[Read more]({{% relref "features/distributed_inferencing" %}})
+
+## Quick Comparison
+
+| | P2P / Federation | Distributed Mode |
+|---|---|---|
+| **Discovery** | Automatic via libp2p token | Self-registration to frontend URL |
+| **State storage** | In-memory / ledger | PostgreSQL |
+| **Coordination** | Gossip protocol | NATS messaging |
+| **Node management** | Automatic | REST API + WebUI |
+| **Setup complexity** | Minimal (share a token) | Requires PostgreSQL + NATS |