> The excellent on device capabilities makes one wonder if these are the basis for the models that will be deployed in New Siri under the deal with Apple….
https://www.latent.space/p/ainews-gemma-4-the-best-small-mul...
2,814 karma · joined December 24, 2016
Working on: https://bule.ai/
> The excellent on device capabilities makes one wonder if these are the basis for the models that will be deployed in New Siri under the deal with Apple….
https://www.latent.space/p/ainews-gemma-4-the-best-small-mul...
I just made a real-time AI (audio/video in, voice out) on an M3 Pro with Gemma E2B. I posted it on /r/LocalLLaMA a few hours ago and it's gaining some traction [0]. Here's the repo [1]
I'm running it on a Macbook instead of an iPhone, but based on the benchmark here [2], you should be able to run the same thing on an iPhone 17 Pro.
[0] https://www.reddit.com/r/LocalLLaMA/comments/1sda3r6/realtim...
[1] https://github.com/fikrikarim/parlor
[2] https://huggingface.co/litert-community/gemma-4-E2B-it-liter...
Since it's much easier to port source code to other languages now, I'd love to see more projects like written in Swift, or C#.
AFAIK the current model is on par with with Qwen-3-4B, which is from a year ago [0]. There's a big leap going from last year Qwen-3-4B to Qwen-3.5-4B or to Gemma 4.
Apple model is nice since you don't need to download anything else, but I'd rather use the latest model than to use a model from a year ago.
https://machinelearning.apple.com/research/apple-foundation-...
In ChatGPT right now, you can have a audio and video feed for the AI, and then the AI can respond in real-time.
Now I wonder if the E2B or the E4B is capable enough for this and fast enough to be run on an iPhone. Basically replicating that experience, but all the computations (STT, LLM, and TTS) are done locally on the phone.
I just made this [0] last week so I know you can run a real-time voice conversation with an AI on an iPhone, but it'd be a totally different experience if it can also process a live camera feed.
I first tried the Qwen 3.5 0.8B Q4_K_S and the model couldn't hold a basic conversation. Although I haven't tried lower quants on 2B.
I'm also interested on the Apple Foundation models, and it's something I plan to try next. AFAIK it's on par with Qwen-3-4B [0]. The biggest upside as you alluded to is that you don't need to download it, which is huge for user onboarding.
[0] https://machinelearning.apple.com/research/apple-foundation-...
There were/are a lot of discussions on how the harness can affect the output.
For example, last week I built a real-time voice AI running locally on iPhone 15.
One use case is for people learning speaking english. The STT is quite good and the small LLM is enough for basic conversation.
Even though it's more troublesome to submit apps to App Store, it's one signal that the app is not a malware.
https://vercel.com/changelog/cve-2025-55182
> Cloudflare WAF proactively protects against React vulnerability
Update: They do similar thing. Mentioned here [1]
At the same time I'm worried about how the internet is becoming even more centralized, which goes against how it was originally designed.
Our current world is build on top of open source projects. This is possible because there are a lot of free resources to learn to code so anyone from anywhere in the world can learn and make a great piece of software.
I just hope the same will happen with the AI/LLM wave.