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Show HN: Off Grid – Run AI text, image gen, vision offline on your phone

113 points by ali_chherawalla

by sangaya

1 subcomments

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.

by numpad0

1 subcomments

Hasn't here been few of those already eg [1][2]?
1: https://github.com/a-ghorbani/pocketpal-ai
2: https://github.com/shubham0204/SmolChat-Android

by resonious

1 subcomments

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.

by bkmeneguello

2 subcomments

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

by jeroenhd

1 subcomments

Looks useful, though something went wrong doing NPU image generation on my phone.
Reminds me a lot of https://github.com/google-ai-edge/gallery which is a proof-of-concept app by Google themselves for their AI libraries. However, your app supports more and larger models without having to manually import anything, which is very useful.

by nine_k

2 subcomments

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

by willx86

1 subcomments

I like it, I have a couple minor things (android)
Markdown rendering would be great Letting me download a model, wait for it, then. tell me I can't run it safely in my ram feels like it could've told me at the beginning
Bar that nice! Was it annoying integrating with apples AI stuff?

by flyingkiwi44

1 subcomments

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

by isawczuk

1 subcomments

I was looking for something like this. Are you open for contributions?

by romperstomper

2 subcomments

Are there any nice TTS models? It could be handy to have them as well.

by vachina

2 subcomments

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

by derac

1 subcomments

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.

by snicky

1 subcomments

GitHub Releases link is broken.
The dash in "off-grid" is missing.

by ruthlesssavage

1 subcomments

Game-changer.Just downloaded it and wow,this is the future. It’s incredible to have this much power fully offline. No lag, no privacy concerns, just pure utility. I’ve been playing with the vision AI all morning and it hasn't crashed once. 10/10. I have also used other GitHub projects but this feels premium, faster and optimised. Thank you for this!

by ucguy4u

1 subcomments

tried this on pixel 9, interesting stuff

by chr15m

1 subcomments

This rules. Godspeed!

by noodletheworld

8 subcomments

Nice idea, but isnt this kind of daft?
There are basically no useful models that run on phone hardware.
> Results vary by model size and quantization.
I bet they do.
Look, if you cant run models on your desktop, theres no way in hell they run on your phone.
The problem with all of these self hosting solutions is that the actual models you can run on them aren't any good.
Not like, “chat gpt a year ago” not good.
Like, “its a potato pop pop” no good.
Unsloth has a good guide on running qwen3 (1), and the tldr is basically, its not really good unless you run a big version.
The iphone 17 pro has 12GB of ram.
That is, to be fair, enough to run some small stable diffusion models, but it isnt enough to run run a decent quant of qwen3.
You need about 64 GB for that.
So… i dunno. This feels like a bunch of empty promises; yes, technically it can run some models, but how useful is it actually?
Self hosting needs next gen hardware.
This gen of desktop hardware isnt good enough, even remotely, to compare to server api options.
Running on mobile devices is probably still a way away.
(1) - https://unsloth.ai/docs/models/qwen3-how-to-run-and-fine-tun...

by imposter

0 subcomment

[dead]

by wittlesus

4 subcomments

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.