EdgeLM runs language models directly on your device — private, offline, and shared by every app. Download a model once; any EdgeLM-powered app can use it.
No cloud · no account · no tracking · works offline
Most AI apps send your words to a server. EdgeLM keeps everything on the phone — faster, private, and free of per-request cloud costs.
Your prompts and the AI's replies never leave your device. No cloud, no account, no tracking, no ads.
Once a model is downloaded, EdgeLM runs with no internet at all — on a plane, in a tunnel, anywhere.
One model, loaded once and served to every app — so a second app adds almost no extra memory.
Nothing to pay per request and no network round-trips. The compute you already own does the work.
EdgeLM guides you through setup and recommends the right model for your phone.
A quick welcome explains how on-device AI keeps your data private.
EdgeLM suggests the best model for your phone — one tap to download. Power users can switch to Advanced for the full catalog.
Try it instantly in the built-in playground. Any EdgeLM-powered app on your phone can now use AI.
Plain-language by default — download the recommended model and chat. Full model details and controls are one tap away in Advanced.
From tiny-and-fast to more capable — each shown in plain language with its size and what it's best for, and a warning if your phone may not have enough memory. Keep several installed and switch instantly.
Fast and light — quick questions and short replies on any phone.
A well-rounded helper for chatting, writing, and summarizing.
Sharper answers and better with other languages.
Higher-quality writing and thinking. Best on newer phones.
Best for tricky questions, math, and coding help.
EdgeLM is a shared runtime — your app calls it instead of bundling and managing model weights. Add the SDK and stream tokens with an OpenAI-style API.
// build.gradle
implementation("ai.edgelm:sdk:0.1.0")
// stream a reply — runs entirely on device
EdgeLM.chat(
prompt = "Explain on-device AI",
sessionId = "chat-1"
) { token -> append(token) }
// graceful if the runtime isn't installed
EdgeLM.promptInstall(context)