Your phone has a GPU more powerful than most 2018 laptops. Right now it sits idle while you pay monthly subscriptions to run AI on someone else's server, sending your conversations, your photos, your voice to companies whose privacy policy you've never read. Off Grid is an open-source app that puts that hardware to work. Text generation, image generation, vision AI, voice transcription — all running on your phone, all offline, nothing ever uploaded.

That means you can use AI on a flight with no wifi. In a country with internet censorship. In a hospital where cloud services are a compliance nightmare. Or just because you'd rather not have your journal entries sitting in someone's training data.

The tech: llama.cpp for text (15-30 tok/s, any GGUF model), Stable Diffusion for images (5-10s on Snapdragon NPU), Whisper for voice, SmolVLM/Qwen3-VL for vision. Hardware-accelerated on both Android (QNN, OpenCL) and iOS (Core ML, ANE, Metal).

MIT licensed. Android APK on GitHub Releases. Build from source for iOS.

Putting the power and the data of the users in the hands of the users themselves! Well done. Getting it setup was easy. Wish the app recognized the keyboard and realized when it was displayed so the bottom menu and chat box weren't hidden under it.

On my Samsung phone it doesn't move the screen up to make room for the keyboard so I can't see what I'm typing.

Really awesome idea though. I want this to work.

Is there something similar, but geared towards a Linux desktop / laptop? I suppose this would be relatively easy to adapt.

Very nice, but I'm gonna wait for the f-droid build.

The repository is listed as offgrid-mobile everywhere on that page but is off-grid-mobile.

So the lastest releases is at https://github.com/alichherawalla/off-grid-mobile/releases/l...

And the clone would be: git clone https://github.com/alichherawalla/off-grid-mobile.git

This is genuinely exciting. The fact that you're getting 15-30 tok/s for text gen on phone hardware is wild — that's basically usable for real conversations.

Curious about a couple things: what GGUF model sizes are practical on a mid-range phone (say 8GB RAM)? And how's the battery impact during sustained inference — does it drain noticeably faster than, say, a video call?

The privacy angle is the real killer feature here IMO. There are so many use cases (journaling, health tracking, sensitive work notes) where people self-censor because they know it's going to a server somewhere. Removing that barrier entirely changes what people are willing to use AI for.

Ok it lists the instruction to build for iOS, but how to sideload?

I haven't run it, but I looked through the repo. It looks very well thought out, the UI is nice. I appreciate the ethos behind the local/offline design. Cheers.

GitHub Releases link is broken.

The dash in "off-grid" is missing.

This rules. Godspeed!