They are a hardware company and will keep selling the best machine for AI use. Well done.
I think Evans is completely wrong. There are only 2 truly frontier models. (at least for now). And Anthropic seems to be leaving OpenAI behind so there might be only 1 in the near future. (which is scary/dangerous)
Extremely tangential, but this is my favourite upshot of AI. For decades, companies have been walling off their services and forcing us into their fuckass UIs. Now over the course of the last twelve months, suddenly everything has an MCP and I can use it through my command line chat interface.
Any company that doesn't adapt gets so hammered by people's AI-DIY web scrapers that they have no choice but to cave.
But we can imagine that the balance of what's on-device vs what's remote will move continuously towards the former as time, improved HW and improved local models keep progressing
From a user’s perspective, it doesn’t matter.
Now if they can further reinforce their angle on Privacy, they might continue to be what they are (or more)
They’re typically a bit better on high TDP stuff, and a bit worse on low TDP. They mostly match in the middle. I have a $500 AMD NUC and a slightly older $2000 MBP. Inference throughput is within 2x.
The comparison is a little messy: AMD currently maxes out at 128GB of RAM vs Apple’s discontinued 512. Apple has nothing to rival the Steam Deck.
Android succeeded at this to an extent with phones, but Apple has been able to keep its products differentiated enough in the minds of consumers to maintain their premium pricing. So far.
I'd love using Gemma4 as an example. but thinking of a user. if 10 Apps each uses same model and downloads it, the phone will be bloated.
I still didn't understand if Apple provided a way for multiple apps uses same on-device model (without tricky namespaces and permissions).
I didn't see anything suggesting that's the case.
They were wrong when their on-device model was way behind. They still might be right in the long term.
While multiple app I use might need Gemma 4 E4B, I use dozens of apps and app devs can choose from hundreds of models. A shared cache might reduce size a little when there's overlap, but the core problem still exists. If each app chooses a model disk and memory-swapping explode.
Its probably be better for device manufacturers to bake in a default. I'm not proposing they limit you from using others, but one shared default might be best developer/user experience for 99% of apps.
- Being warm in memory is the single biggest perf speedup you can get, and a default is much more likely to be warm.
- "Best model" is usually "best model for this device" given both RAM and compute. A developer can't test every device but Apple can/will.
- Each model needs to be optimized for the hardware (what's running on ANE, what's running on Metal, what's running on CPU). The default gets optimized.
- If you need custom model, a Lora is probably best (30MB, benefits from all of the above)
You could say the default should be swappable, but that's more a linux ideal than an Apple one so I doubt we ever see that. Plus there are real downsides: intentional or not, prompts end up optimized to the model they are developed for, so swapping the default system model would degrade every app.
- Application can ask for specific model, if available use it. if not, ask to download it (or try some fallback / alternative)
- User can manage models. So as a user I can clean unused models (and for non-techie have something similar to offloading apps when unused for some period of time).
The framework's whole deal is that it lets you use the same API to target either the device built-in models, the Apple-hosted online models (Private Cloud Computer), or write your own shims to call out to arbitrarily hosted online models.
You can then dynamically route your calls to a different kind of model/provider, using system APIs, without having to write your own abstraction layer over "I want to use local model for this, but I want to use Claude for that", or having to integrate your own API integration with Anthropic/OpenAI APIs.
It abstracts things like tool calling in one place; and has a bunch of other niceties/oddities (it keeps the same "transcript" going, even if you dynamically switch providers/models during a session) and some other things.
> Requests go directly from your app to the Claude API; Apple is not in the request path and does not see prompts or responses. Usage is billed to your Anthropic account at standard API pricing. Your app decides when to use Claude and when to use Apple's on-device model: pass whichever model you want to each session.
Lol bro this is literally it this is the model they've been training (was Apple Foundation model not a big enough hint?)
Ahh I was hoping for the opposite: all of the existing features of Claude Code but somehow running locally on my laptop's neural engine. A pipe dream on an M2 with 8 GB of RAM, but I had a flicker of hope there.
https://developer.apple.com/videos/play/wwdc2026/232/ https://www.youtube.com/watch?v=wykPErJ8M-8
In 10 years, I hope my MacBook Pro can run today's frontier models and has 1TB of unified Memory.
You can use environment variables to have claude code query literally any endpoint you choose as long as it has a compatible API.
..but instead we get Claude, hosted who-knows-where. maybe in X-AI datacenters? maybe in Amazon somewhere? who knows..
"You pay an indeterminant amount of money to ask a question and you might not even get the response you want without spending even more money" doesn't appeal to most people who aren't gamblers and explaining how "thank you" at the end of a long exchange can be expensive due to context is an even harder thing for an average person to swallow.
Token cost going up/down like a yo-yo also doesn't help. Normal users NEED fixed costs and don't want to expend energy constantly keeping up with the AI meta. "My subscription lasted much longer last month" isn't a winning problem either.
I think Apple is correct that Local LLM for most things is the future.
Right now for allihat.com I just let people use the Apple model locally if you don't feel like using the claude key. And my conversions to paying user shot up like 3x! But it really isn't a replacement obviously to claude. I was hoping Apple would make proxying to Claude some kind of thing they do for me so I also don't have to proxy to my own server just to try and manage API to Claude usage.
Apple is offering developers with less than 2 million downloads free AI models via their servers https://techcrunch.com/2026/06/08/apple-bets-cheaper-ai-will...
With other words, it's unlikely to happen as there is no money in it. Better for Apple to create some new subscription "AI" and "AI-lite" plans people can subscribe to, and since Apple is a company and we all know what those care about, it's unlikely to become a utopia of local models running on your phone.
> At WWDC, Apple announced that it's opening its Foundation Models framework to third-party cloud model providers. Starting with iOS 27, macOS 27, iPadOS 27, visionOS 27 and watchOS 27, model providers can implement the new public LanguageModel protocol to provide a common interface for model inference. We've made Gemini models available to the Foundation Models framework through the Firebase Apple SDK.
This provides a fully native development experience — cloud-hosted Gemini models can plug directly into the Foundation Models framework using the same API. That means the on-device Apple model and cloud-hosted Gemini models sit behind a shared API surface, so you can easily swap between local and cloud inference to fit your use case.
https://blog.google/innovation-and-ai/technology/developers-...
Protocol in this context means a Swift language feature, like interface in some other languages: https://docs.swift.org/swift-book/documentation/the-swift-pr...
Layers are luxury and remove control and transparency.
so Claude via FM dies offline while Apple's on-device SystemLanguageModel (the ~3B one) keeps working. It isn't a hybrid really: the framework just has both implement the same LanguageModelSession protocol so "local 3B" and "remote frontier model" become a one-argument swap.
IMHO what's worth internalising is that the two share an API but nothing else: the on-device path runs on Apple's Neural Engine and costs battery (you can watch ANE power ramp while it works) while the cloud path costs API credits/tokens and does zero local compute. Same code, opposite cost model.
I know this is from a developer perspective. But as a consumer this is just funny.
Proxy (production)
For production, route requests through your own back end with .proxied. The relay at baseURL adds the Claude API credential server-side, so the app ships no key. The headers you provide are sent on every request so your proxy can authorize the caller.
https://platform.claude.com/docs/en/cli-sdks-libraries/libra...
Special emphasis on the "isn't compiled in yet" and "or construct one" bit.
While expected, it’s still a bummer.
They are.
Enough is enough. I’m seriously evaluating open models this week.
Then Apple quietly refuses to participate by not investing tens or hundreds of billions in creating a competing LLM. Sure, they resell Claude for the marks or utilize Gemini to placate the gullible fools but they know what's up.
https://www.microsoft.com/en-us/microsoft-copilot/for-indivi...
It's also smart for them to make sure the billing is going direct from Anthropic to the developer. The initial thought is "That means Apple's not taking a cut", but from the other side of it, developers who use this API are going to have to expose that cost to customers somehow, and that translates to subscription/InAppPurchase etc. on top of which Apple will get it's 30%.
What confuses me about this article is: The code examples Python, Ruby, etc.) look to me like the original Anthropic APIs, not Apple’s abstraction. Did I miss something?
Seems that the UX will be enough to win over users and investors
I don't like this model. Then all the user data is visible to the proxy.
Far better would be some kind of micro payment architecture where a wallet is on the users device and coins are attached to each request.
We just need to live in the alternate universe where micro payments succeeded.
Apple's Foundation Models framework (shipping in iOS 27 / macOS 27 this fall) is the standard Swift API for on-device AI — the same API Apple uses for their own small model. This package makes Claude plug into that same API as a drop-in swap.
// Apple's on-device model
let session = LanguageModelSession(model: SystemLanguageModel.default)
// Claude — same API, just different model constructor
let session = LanguageModelSession(model: ClaudeLanguageModel(name: .sonnet4_6, auth: auth))
You don't call the Anthropic API directly. Apple's framework handles streaming, tool calling, and structured output (@Generable) — you just get Claude's capability through it.