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  1dom
  This is a cool way of approaching AI models. I'm a big fan of local LLMs, local specific models like this should be even more powerful.> Every model is free up to 100k monthly active devices. No tokens, no logins.I dunno about the business model though. Cloud LLM billing makes sense: you're getting another computer to do work with each request, and using their compute via their gateway that they bill you.These local models are like old school software. They're producing the weights, and then giving them to people. If I'm happy with the weights you've given me, and I'm not using your compute for inference and not wanting or needing any updates off you, why should you continue getting money off me and my customers?The whole "but we need to keep it updated for your security" doesn't really work as well for software designed to run fully offline like these local models are.I'm not saying they shouldn't get paid, but I guess I feel a personal sadness that it's less obvious how to successfully monetise such a sincerely useful and beneficial approach towards AI models.
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  nater5000
  I definitely think there's a lot to be done with small models dedicated to specific tasks. I've always thought the REAL value is in having large models be able to easily build small models for custom tasks (which I know is kind of a thing), but perhaps just providing the small models directly is the more accessible approach.>accessible via one SDK for Swift, Kotlin, and JavaScriptLol well let me know when there's a Python SDK and I'll give it a try then. Obviously this isn't a deal breaker if you have a real case, but as someone who is willing to spin something up and try it out if there's a quick "pip install" command, this is getting put back on the shelf for now.
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  mtlynch
  I love this idea and hope to see more on-device models. How do they make money, though?I tried out their demo for Clear, the audio quality improvement model.[0] I'm not sure if it's just I don't have refined enough an ear or their demo is broken, but the "raw" and "enhanced" versions sounded exactly the same to me.[0] https://desertant.com/models/clear/
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  sipjca
  at first i got very excited about a new fast transcription model (voz) but turns out its just parakeet v3 with some new inference code which is macOS/iOS specific
• viccis
  I wish we could pop a tiny one into my phone so that when I type "Will see you" and swipe the word "later" it chooses that instead of "lasso"
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  ashenke
  A lot of the models would be useful in a web context, to improve on the CMS we're making for clients. But they look like most of them are iOS only, few have a node package or something other, and all the benchmark are running it on modern iPhones so I doubt it would be that fast on a 20$ VPS.
• faangguyindia
  Cool! is there a local model for LLM command approval?
• lukevp
  I would love to use Voz and Ear, but I’d need a version that is competitive with other audio transcription LLMs for platform availability - meaning macOS, Windows and Linux, and supporting GPUs if available.
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  library8848
  Shiny layer of marketing and proprietary code on top of open models?Voz is Parakeet 0.6B v3Clear is DeepFilterNet 3Ear is the language predictor from whisper-tiny...
• init0
  Awaiting web version...
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  markdog12
  > opinionated on-device intelligence> Hate speech triage. On-device moderation that flags hateful, abusive and threatening textWhat could go wrong here?
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  nullbio
  This is a cool idea. The most useful one for me would be something that can process pdf files into a json schema. Title and tag generation from a post would also be useful. I'm interested in web app though.
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  illright
  I wonder why they only support Apple platforms, citing CoreML. Doesn't Android have a similar framework, ML Kit?
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  bronlund
  The website looks amazing.
• asamadx
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• anon
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