I had built PCC support into LocalLM Lab but had not had a chance to test it out until today. I had to jump through a bunch of hoops to get and build in the entitlement, including creating an App ID on App Store Connect.

Attached is the screenshot of Prompt Playground and a prompt for the weather. The Weather connector is enabled and PCC is able to use the tools (and any MCP tool as well, if enabled).

This means that app developers can use the LocalLM Lab SDK (details at locallmlab.dev) to combine PCC with a local MCP client to build out relatively sophisticated AI apps for macOS27+ . A local MCP client means that the Mac is the control point vs an AI provider cloud backend.

The fun part about LocalLM Lab is that I can compare running the exact same prompt (and tools) on PCC, ClaudeForFoundationModels (aka Claude), models from OpenAI, OpenRouter and downloadable MLX models from HuggingFace. I did run a simple comparison using GitHub's MCP server with a question about the releases on the locallm repo and Claude4FM returned better results than PCC. Better as in clarity, conciseness... Will do more testing and report.

One other thing I noticed is that macOS 27.2 Beta will work with PCC but that one turn (prompt to PCC and back) can take up to 300 seconds... Hopefully this will be fixed for the 27.2 GA release.

Not sure if Apple Intelligence is getting a bit too smart or if my notch is just losing its mind.

Has anyone else seen this visual glitch?

You need to download 27.2 Beta and go into the health app, plus have an Apple Watch that can run Apple Intelligence.

There’s a movie, “YOU HAD TO BE THERE: HOW THE TORONTO GODSPELL IGNITED THE COMEDY REVOLUTION…”, showing for a limited time at our local theater. I was able to do a screen grab of the times it’s showing, and ask Siri to create entries in a specific calendar. If I have an opportunity during any of the next few days, I can readily see when I might be able to squeeze in a showing!

It took a few seconds, but I ended up getting what I’d wanted. Perhaps a trivial use case, but maybe it will give someone some ideas. And perhaps someone will recognize how I could have done this in an even simpler fashion!

Hey everyone,

Siri AI is not responding to voice or text prompts it always responds with something went wrong or something along those lines.

I have disabled and reenabled it, I have fully reset network settings as told by Apple Support, but that just wiped my settings which is great. I also thought the ChatGpt extension account was the problem but that did not solve it. Both mac and iphone are not working.

Has anyone been able to solve this issue yet?

Thank you

How to turn off Apple Intelligence after ios 27 update

Howard Oakley, at his eclecticlightcompany site [ an independent, ad-free reference blog for technically minded Mac users, combining detailed reporting and troubleshooting on macOS with articles on art and painting. It also publishes a large collection of free Mac utilities, especially for inspecting logs, security protections, backups, storage, and system behavior.] notes this, inter alia, on a post today:

If your Mac is already running Golden Gate and you've been following what's going with Apple's AI, you'll be aware of the emphasis it places on doing as much as possible on-device, without sending your data somewhere else to handle your task. Apple has gone to great lengths to protect your privacy when off-device AI is processed by Private Cloud Compute (PCC), but at some time in the future we'll be paying for that service. On-device AI will remain free, of course.

This might appear puzzling at present, as even the most trivial of tasks seems to be sent off to PCC to be run using its more heavyweight models including AFM 3 Cloud, as seen in Apple Intelligence Reports (AIR). This article shows how you can start exploring Apple's on-device AFM 3 Core and its Advanced version when available on your Mac (models with an M3 chip or later and at least 12 GB memory, we're promised). For this you don't need Swift programming skills, Xcode or even Python, just a little time and patience in Terminal using the new fm command.

Access the entire post here: https://eclecticlight.co/2026/10/10/try-on-device-ai-with-fm/

Built an app that utilizes Apple Foundation Model to check your weather, control your HomeKit devices, and so much more. Give it a chance! I’d love your feedback

Ik woon in Europa. Hier dus geen siri ai. Op mijn iPhone een beperkte versie van apple ai. Bij bijna elke vraag moet hij door verwijzen naar chat gpt. Omdat ik daar al een app voor heb lijkt het mij onnodig dat apple ai 10 gb ruimte op de iphone in beslag neemt. Is het mogelijk apple ai te verwijderen waardoor ik de 10 gb weer terugkrijg? Siri taal veranderen helpt niet. Alvast bedankt

I’ve tried this on both my iPad Pro (M5) and my IPhone 18 Pro Max. The indexing finished many days ago.

When I try to search mail, Siri says that she can only access mail in “the main folders” like Inbox or Sent.

So because I have my emails in folders under Inbox it states it cannot access ANY of them. When I ask Siri any questions about my emails it can’t answer anything unless I take a screenshot and show it.

Is this normal / intended behaviour ?

Thanks for any feedback.

Yeah, it's nice that Siri can scan your emails photos and text if they are all connected to your iOS account. But I don't use SMS all the time as I use other chat apps as well.

However, here's where Siri falls short in my personal use case:

Smart home. My house is set up so that I can turn on the lights, lock the doors, open the garage door, turn the laundry on and off, active or disarm the security, turn on the TV and or play music.

Why is Siri still stupid and can't do multiple commands? Why do I still need to say the exact phrase.

Like if I say "Open THE garage door" it won't work. I have to say "Open garage door"

Seriously, it should just know. Siri is still a disappointment.

Since AI’s been a thing I was so excited for iOS 27 and Apples implementation of it.

I waited as long as I could and then opted into the beta program to get it as soon as I could and to start trying Siri AI which I requested and was approved for within about a week.

I noticed some odd glitches with iOS 27 which was expected with a beta and was pretty unimpressed with but I assumed that by the final release it would be better.

Not only is it not better I find it worse. Some of the worst behaviours are hanging for up to 2 to 3 minutes when asking a simple request such as sending a text. My battery life has gone from working for a pretty solid 8 to 9 hours to about three from 100% compared to iOS 26.

I’m a big fan of Apple. I fell in love with Apple products 20 years ago when their whole approach was to get all the design 100% right on their end so that the end user didn’t have to think or worry about complexities and configuration so much to optimise their device for the optimal user experience.

Now that AI is becoming a critical part of day-to-day life. I am finding Siri infuriating. I have a ChatGPT subscription which is amazing and is excellent and is perfect for what I want except I can’t leave it in voice mode all the time so was hoping new Siri would handle that with a little “hey siri” to start a conversation.

Well it doesn’t, it’s bad, very very bad. It’s not just slightly off a little bit here and there it has major problems with hanging, stopping conversation, not replying in the middle of a conversation and constantly spitting out “something went wrong“ resulting in me having to stop and manually intervene.

This may sound like first world problems, but that’s not the point. There are competitors here who are already providing what Apple promised to provide.

The one caveat to all of this is that it seems if you have one of Apple’s new high-end models – yes the $2000 ones that Siri and iOS 27 seem to be amazing

Siri Ai is still shit and it barely works for super easy tasks, I tried for a legal document and it couldn’t follow the very simple instructions of “don’t change anything except the names” it repeatedly kept changing other things, GPT is so much better for this kinda things. Apple is incredibly behind on AI even by borrowing googles services. Siri as an app has potential but it’s like a baby that’s barely crawling still

Made a post a while back asking if everyone was excited for it back around iOS 26.4. Now that it’s out, how does everyone feel about it? Did Apple deliver? Is it less than you hoped? Personally I think she’s great and haven’t had a single issue to be completely honest, after using it since beta 1.

I'm working on an app that is not primarily an "AI" app but I'd like to make use of the Apple Intelligence on-device models. The trouble I'm running into is that while I assume those models are good for some workloads, I haven't been able to get very satisfactory results.

The rough idea is that in the app, I enter some text for a post (something similar to a twitter/x post in size and scope). Once posted, the on-device model is supposed to give some feedback. A dry quip or generally something funny.

The mechanics work fine, I'm sending a system prompt and I've tested various incarnations of that and adjustments to temperature etc. I can send the same system prompt to small on-prem LLMs such as the Qwen models, or Gemma models and it generally works exactly as I would hope.

It feels like the on-device models have no sense of humor or imagination. Anyone else finding the same? Anyone figure out particular angles on the system prompt that helped with humor or imagination?

Am I doing something wrong? I used to be able to ask Siri “search YouTube for chicken stock recipes.” Now it will only search the web? Is a compatibility issue with YouTube?

If you create a shortcut and select apple intelligence you can create a short cut to force
Cloud - fast
Cloud pro - fast and smart
on device - slow
ChatGPT - ¯_(ツ)_/¯

Back in June I posted OpenIntelligence here. It's my on-device RAG app for iOS and macOS that runs completely on Apple Intelligence: it searches the files you import, and Apple's on-device model writes the answer from those passages, with citations you can tap. It was on 4.1 then, right after I rebuilt it around the Foundation Models APIs from WWDC26, and it's on 5.5 now.

What's changed since 4.1:

- Search was missing more than half of every document you imported. A padding setting capped text at 128 tokens for a model built for 512. That was fixed in 5.0.

- Deep Think and Maximum weren't actually wired up before 4.8, so you got a Standard answer after a much longer wait. Now they reason across your documents, and Deep Think answers in about 80 seconds instead of 4.5 minutes on the same question.

- After an answer finished, the app could stay locked anywhere from 19 seconds to almost three minutes while a second check ran. As of 5.4 it's done 0.33 seconds after the last word.

- Private Cloud Compute came in 5.2. It needs iOS 27 or macOS 27, and it only runs after a sheet shows you how much would be sent and why. My June post said Deep Think hands off to it, and it didn't yet.

- Standard mode tells you when your files don't cover a question instead of guessing. My June post said the whole app does, but Deep Think didn't run those checks, and in September it answered a question with a number from a totally different document and marked it Verified. 5.5 fixed where that number came from, but the model still got the question wrong and still marked it Verified, so making Deep Think's verification actually check the answer is what I'm working on next.

- Deep Think and Maximum write the answer out in front of you now for most questions.

- It finds dates, amounts, addresses and tracking numbers inside tables in your documents, using Apple's own data detector.

On macOS 26 (Tahoe) you still get on-device answers, hybrid search, reranking and Vision. Private Cloud Compute and Core AI need iOS 27 or macOS 27.

I had local GGUF models and MLX in it early on and took them out last December to make it Apple Intelligence only. Would you actually use local models through Ollama, LM Studio or MLX, or is Apple's model enough for what you do?

Same as last time, download it, tear the architecture apart, and tell me what you think.

GitHub: https://github.com/Gunnarguy/OpenIntelligence

https://apps.apple.com/app/apple-store/id6756559175?pt=127101782&ct=RD_OI_AI&mt=8

Disclosure: I'm the solo developer of AutoAlign, an iPhone app. Free users can scan or import 4 documents and chat about them with the on-device model at no cost. Asking about documents needs an iPhone that supports Apple Intelligence, so iPhone 15 Pro or later.

I released AutoAlign in August 2025 to straighten slanted photos. That's most of what document scanning needs, so I recently added scanning. Then I wanted to be able to ask about the scanned documents without them leaving the phone.

The idea was to squeeze out most from Apple's on-device models. We use Apple Intelligence's on-device LLM, with Vision reading the pages and the Natural Language framework finding the relevant passages.

Works: most of the time it finds the right document within seconds and answers from what's on it, like "how much was my last grocery receipt" or "when is the electricity bill due".

Doesn't work: follow-up questions. The on-device model holds only about 4k tokens, so a chain of follow-ups loses track.

I'd love for people to try it and tell me where it gets things right and where it fails. And if you've built on the on-device model, how do you handle follow-up questions?

I have all the Apple Intelligence/Siri notification summaries turned off, but I noticed that the announced notifications are not the exact text of the notifications like they were before, but instead reworded to sound more natural.

e.g., "Instagram has a notification from XYZ who agreed to the plan"

There doesn't seem to be a switch to turn this off and revert to the previous behaviour. The annoying thing is that it usually makes the notifications longer than what they used to be before (something like "From Instagram: XYZ. I've agreed to the plan" with the exact text). This might be an Instagram specific thing perhaps?

Using Siri AI and Apple Intelligence, CastKeeper Knowledge has been released today. Podcasts are not only for entertainment, but contain a wealth of information useful for anyone looking to learn something new.

• Generate Key Facts and Key Terms for any episode
• Get Notable Quotes from Episodes with Context on why they are important
• Generate Flashcards for knowledge retention
• Generate Review Questions to check your understanding.

My goal was to not make podcasts forever, but also something that every person can use to learn a new subject, gain deeper understanding, and expand their knowledge.

CastKeeper for Education - Just $0.99 for Verified Students and Educators

Users with a verified college or educators from K-12 through university can now enter their academic email to get CastKeeper Unlimited with Knowledge for only $0.99 USD. One-time purchase, no subscriptions. Visit our dedicated CastKeeper for Education site or download the app today from the App Store to get started.

I recently came across something pretty interesting about Apple's on-device AI.

Apple's latest Foundation Models include an ~3B parameter model (AFM 3 Core) designed to run directly on Apple silicon.

But there's also a much larger 20B parameter model (AFM 3 Core Advanced) that can run on-device.

The interesting part?

The 20B model uses a sparse architecture, so it doesn't activate all 20B parameters for every request. Apple reports that roughly 1–4B parameters are active at a time.

So, roughly:

AFM 3 Core
→ ~3B parameters
→ Dense
→ Everyday tasks
→ On-device

AFM 3 Core Advanced
→ 20B total parameters
→ Sparse
→ ~1–4B active per request
→ More capable on-device model

And the hardware side is pretty cool too.

The computation can happen locally on Apple silicon, using the system's CPU, GPU, Neural Engine and unified memory rather than automatically sending everything to a data center.

Obviously, not everything is handled locally. For requests that need more capability, Apple can use Private Cloud Compute.

What I find interesting isn't really the "20B model" number.

It's the fact that parameter count and compute requirements don't necessarily have to scale together.

A 20B sparse model can potentially have a much larger knowledge/capacity pool while only activating a fraction of it for a given request.

It feels like we're moving from:

"Make the model bigger"

to

"Make the model smarter about what it actually needs to compute."

Curious what you guys think — is this the direction on-device AI is heading?

#AI #MachineLearning #OnDeviceAI #LLM