What's the hiring space and business strategy around all of these smaller AI labs? Its really cool that people like these guys get paid to optimize models and give them out for free (open source). Do a lot of these labs have forward deployed engineers doing integrations with customers who want local models? Is there a general shift towards the local model crowd?
If you read to the bottom of the page, it says they're funded by a few people, and one of them is Samsung. I'm betting Samsung wants to be able to ship a capable AI system on a future model of their phone so they can compete with Apple.
Bonsai 27B: A 27B-Class model that runs on a phone
81–90 of 278 posts
Re: Bonsai 27B: A 27B-Class model that runs on a phone
#82This must be some sort of unpublished app? I can just see their image tool on the app store
It's a LLM model, not a phone app. Available on HuggingFace: https://huggingface.co/collections/prism-ml/bonsai-27b
The article is about running it on a phone though, and shows an app with their branding running this in text mode on a phone. I'm asking where can I find this app to try what is being demonstrated in this article & video? Appstore only has an image gen app by them and other MLX apps I've tried don't seem to support this model
Re: Bonsai 27B: A 27B-Class model that runs on a phone
#83Apparently Apple is "in talks" with the PrismML: https://www.cnbc.com/2026/07/14/apple-prismml-ai-compression...
Notably, PrismML CEO Babak Hassibi told CNBC this, so it’s either (1) bullshit, or (2) he just ended any chance of a relationship by leaking news of the talks.
apple’s secrecy agenda has been defeated to an extent by the practicalities of ubiquitous technology?
Re: Bonsai 27B: A 27B-Class model that runs on a phone
#84Earlier quoted context omitted.
Orinth was not impressive in my vibes testing, I just completed my first grid analysis with real evals on qwen 27b. I can now scale that grid analysis and intend to include the qwen 9b ftunes I've seen going around. They were actually a main motivation because so many claim this or that one is better, but very little in the way of evals
I tried it, too, and it got stuck in some loops where it couldn’t recover. Shame, it was promising for the same reason as Bonsai’s models.
huggingface.co/Tivaphraen/Geryon-9B-v1
Re: Bonsai 27B: A 27B-Class model that runs on a phone
#85Tried it on Android and got "!!!!!!!!!!!!!" for answers.
The qwen models really seem to have this as a failure mode, its so annoying having a proper trace ending up in !!!!!! Garbage.
Sounds like the model is not following a proper probabilistic choice here, so maybe more a programming error than a model training error.
Re: Bonsai 27B: A 27B-Class model that runs on a phone
#86Re: Bonsai 27B: A 27B-Class model that runs on a phone
#87Earlier quoted context omitted.
Notably, PrismML CEO Babak Hassibi told CNBC this, so it’s either (1) bullshit, or (2) he just ended any chance of a relationship by leaking news of the talks.
Apple would punish him severely unless they cleared it in advance, it might be to their advantage for some reason (negotiating with Google for Gemma rights? idk).
Re: Bonsai 27B: A 27B-Class model that runs on a phone
#88Earlier quoted context omitted.
I tried it, too, and it got stuck in some loops where it couldn’t recover. Shame, it was promising for the same reason as Bonsai’s models.
check out geyron-9b, I've only used it a bit, but seems better than orinth on vibe evals huggingface.co/Tivaphraen/Geryon-9B-v1
Re: Bonsai 27B: A 27B-Class model that runs on a phone
#89That's awesome. What's the largest model that could fit onto a single 16gb gpu at 1.125 effects bits per weight?
Doing some naive math, the F16 filesize is ~53.8gb, the 1-bit version is ~3.8gb, about 7% of the original size. The F16 size is roughly 2x param count, so that gives a rough ballpark of ~110B.
Re: Bonsai 27B: A 27B-Class model that runs on a phone
#90Earlier quoted context omitted.
The qwen models really seem to have this as a failure mode, its so annoying having a proper trace ending up in !!!!!! Garbage.
Wait in a regular sentence, what is the probability of "!!!" being followed by "!"? Sounds like the model is not following a proper probabilistic choice here, so maybe more a programming error than a model training error.