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Nice project. I thought of building exactly this.

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#.


The big question is whether Apple can keep shipping new models constantly.

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-...


I’m not sure why that’s a question, it’s just a downloaded file. You can even watch it download separately when you enable Apple Intelligence (it’s not tied to OS updates from what I can tell).

Of course I imagine Apple is not going to be the fastest mover in this regard. I’m not even sure they believe the product will be widely impactful anymore and may keep it relegated to a small list of popular use cases like photo touch ups and quick questions to Siri. For me the most useful parts of Apple’s AI don’t even require me to enable Apple Intelligence.


I'm curious about the multimodal capabilities on the E2B and E4B and how fast is it.

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.

https://github.com/fikrikarim/volocal


I just want to say thanks. Finding out about these kind of projects that people are working on is what I come to HN for, and what excites me about software engineering!

Thank you for the kind words!

yeah, it appears to support audio and image input.. and runs on mobile devices with 256K context window!

The E2B and E4B models support 128k context, not 256k, and even with the 128k... it could take a long time to process that much context on most phones, even with the processor running full tilt. It's hard to say without benchmarks, but 128k supported isn't the same as 128k practical. It will be interesting to see.

> In the coming days, we will also open-source smaller-scale variants, reaffirming our commitment to accessibility and community-driven innovation.

This is huge problem for developing countries. Most people here have $100-$200 phones. iPhone is a luxury.

Forget developing countries, iPhone is a luxury even in some European countries, when rent is 500+ Euros and your take home pay is ~1000. After all the other bills you're not left with iPhone money, which is why 100-200 Euro models of Chinese brands are doing so well.

It's easier to name the countries where iPhone ISN'T a luxury, as you can count them on very few hands.


[flagged]


Many countries would develop much faster if there weren't bombed nor maintain by puppet dictactors from (economically) developped nations (USA and france keep doing this intensively, while countries like Germany dont mind supporting fascist states). (PS: I'm not woke, not even Marxist).

What country would be the stereotypical example you are thinking of? I fail to find any

From the US point of view only:

Historically, most of Latin America.

Very recently: why was Venezuela attacked by the US?


Latin America isn’t a country and Venezuela wasn’t developing in any sens of the word

Also, why are they trying to do a genocide in Cuba?

Won't matter - if enough people in developing countries can afford iphones, apple will just rise the prices.

The Github repo is only for issue tracker

Wow it's true. Anthropic actually had me fooled. I saw the GitHub repository and just assumed it was open source. Didn't look at the actual files too closely. There's pretty much nothing there.

So glad I took the time to firejail this thing before running it.


Is there anything special here vs. OpenCode or Codex?

There were/are a lot of discussions on how the harness can affect the output.


Not really, except that they have a bunch of weird things in the source code and people like to make fun of it. OpenCode/Codex generally doesn't have this since these are open-source projects from the get go.

(I work on OpenCode)


Depending on the use case, the future is already here.

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.

https://github.com/fikrikarim/volocal


That’s awesome! I’ve got a similar project for macOS/ iOS using the Apple Intelligence models and on-device STT Transcriber APIs. Do you think it the models you’re using could be quantized more that they could be downloaded on first run using Background Assets? Maybe we’re not there yet, but I’m interested in a better, local Siri like this with some sort of “agentic lite” capabilities.

> Do you think it the models you’re using could be quantized more that they could be downloaded on first run using Background Assets?

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-...


Subjectively, AFM isn’t even close to Qwen. It’s one of the weakest models I’ve used. I’m not even sure how many people have Apple Intelligence enabled. But I agree, there must be a huge onboarding win long-term using (and adapting) a model that’s already optimized for your machine. I’ve learned how to navigate most of its shortcomings, but it’s not the most pleasant to work with.

Try it with mxfp8 or bf16. It's a decent model for doing tool calling, but I wouldn't recommend using it with 4 bit quantization.

Brilliant. Hope to see you in the App Store!

Oh thank you! I wasn’t sure if it was worth submitting to the app store since it was just a research preview, but I could do it if people want it.


Totally agree. There are significantly more new apps being released. I've been visiting the /r/macapps subreddit and they're having trouble filtering new submissions. I generally like the direction that they're taking https://www.reddit.com/r/macapps/comments/1ryaeex/rmacapps_m...

Even though it's more troublesome to submit apps to App Store, it's one signal that the app is not a malware.


Wow, this subreddit looks like the apocalypse of vibe coded projects/apps. Kind of similar to what happened to "show HN". Too many ideas, not enough problems to solve, and likely bad implementations. The result is that nobody uses any of the apps.

In AI conversations, people often forget that at the end of a day, an actual human needs to use your stuff.


Thank you!

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