Lemonade AI
Local AI runtime for text, image, and speech — run models on your own hardware, free and private
| What is it | Local AI runtime for text, image, and speech — run models on your own hardware, free and private |
|---|---|
| Pricing | Free |
| Free tier | Yes |
| Platform | Web Application |
| API | Yes |
| Best for | running LLMs locally for chat and coding assistance, generating images from text prompts on your own GPU |
| Domain registered | 2025 |
Data updated Aug. 1, 2026
What does Lemonade AI do?
Lemonade is a local AI runtime that lets you run text, image, and speech models directly on your own computer. It's not a cloud service you subscribe to — it's a free, open-source application you install, and everything stays on your machine. You can chat with it like a typical AI assistant, generate images from descriptions, transcribe audio, and even write code with it. The whole thing runs locally, so there are no API fees, no data leaving your device, and no internet required once the models are downloaded.
Getting started is straightforward. You install Lemonade on Windows, macOS, or Linux (including Docker and Snap options). It gives you a graphical app, a command-line interface, and API endpoints that are compatible with OpenAI's format. That means you can point any app that works with OpenAI's API at your local Lemonade server instead. It also supports the Model Context Protocol (MCP), so agents and coding tools like Claude Code and GitHub Copilot can hook into your local models. You can pull models from Hugging Face or import GGUF files you already have, and switch between inference engines like llama.cpp, ONNX Runtime, or AMD's Ryzen AI depending on your hardware.
Lemonade is ideal for developers who want to experiment with AI without paying per token, privacy-conscious users who don't want their data sent to a cloud, and anyone building apps that need on-device AI. It works well for coding assistants, personal chatbots, image generation, and speech transcription. The community around it is active, and the project is shaped in public — contributions and feedback are welcome.
Key features
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