Lemonade is a local LLM runtime that aims to deliver the highest possible performance on your own hardware by auto-configuring state-of-the-art inference engines for both NPUs and GPUs. The project positions itself as a “local LLM server” you can run on laptops and workstations, abstracting away backend differences while giving you a single place to serve and manage models. Its README emphasizes real-world adoption across startups, research groups, and large companies, signaling a focus on practical deployments rather than toy demos. The repository highlights easy onboarding with downloads, docs, and a Discord for support, suggesting an active user community. Messaging centers on squeezing maximum throughput/latency from modern accelerators without users having to hand-tune kernels or flags. Releases further reinforce the “server” framing, pointing developers toward a service that can be integrated into apps and tools.

Features

  • Local LLM server targeting GPU and NPU acceleration
  • Auto-configuration of high-performance inference backends
  • Simple install and run flow with guided documentation
  • Community support via Discord and active issue tracking
  • Works across research, startup, and enterprise use cases
  • Designed to be a drop-in foundation for local AI apps

Project Samples

Project Activity

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License

Apache License V2.0

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Model Context Protocol (MCP) Servers

Registered

2 days ago