I have a Mac with 4TB of storage but it’s still annoying when every new AI app I try installs its own virtual environment with a fresh copy of Python, PyTorch, other duplicate libraries, and then models on top of that.
The apps can use the system provided on-device model using the same framework and APIs; but there's no affordances to deduplicate custom models between apps.
Is this Apple encouraging developers to go through their api abstraction layer to use LLMs so that when they launch their own (which I think we’ve heard they’ve been spending lots of money on training and might be somehow involved with Siri or current Apple AI?) that they can easily help devs make a seamless transition? Or is it just a developer nicety or something else?
Apple has some clever mechanics to protect user data. I had to work with App tracking stuff lately and their approach to keeping user details private with anonymized cohorts (SKAN, Differential Privacy) before reporting tracking events to third party platforms was surprisingly well thought out. There is value in having them in your loop if you care about privacy.
A dark, but not totally unfair take: It makes it easier for Apple to take payment for the models others provide, and even allows Apple, if they want to, to use the data to build a dataset for training their own models based on how users use third party models. It's only on Apple devices this API is used, so they split up the market by not letting developers use the same system if they want things to work on iOS, locking users even more in.
This is support for a new framework that ships with reality/mac/iPad/watch/tv/iOS 27 (and that they've promised to open-source later in the year, so presumably you'll also be able to lean on this if you ship Swift on your backend).
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.
The cynic (or realist?) in my thinks this abstraction layer is Apple's way of making sure that users give their own Apple Intelligence credit for the underlying LLM functionality, even if another company is actually providing the LLM.
Maybe they plan to have the providers pay for being the default model? So basically, what Google is doing right now for search engines. The difference however is that Google is making money with additional search requests while AIs are (as of now) losing money with additional requests. I don't see the business case for them yet though.
From app developer standpoint why would anyone ship claude keys like that ... or am I missing something? From consumer standpoint - I guess they can use their own keys but it is not something that is very user friendly as you can imagine.
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.
Coding agent itself an imposed layer. Now they are adding one more layer? Many times I think of coding agent as the vendor supervisor from the body shops of the 90's who promise the customer everything under the sky and thrash the poor contractor to deliver. Coding agents consume 10x more tokens just like how body shops charged their customers vs how they paid the contractors. For a simple test, the same task that makes the model to go out of context length when used via a coding agent, runs fine when prompted directly.
Layers are luxury and remove control and transparency.
This seems smart. Apple, despite not really leading in AI themselves, are right on the hot path of where developers are going to yolo slop into the ecosystem. Make a tonne of sense to define a nice clean API that places like Anthropic can build on top of and expose to developers.
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%.
While I'm happy with Apple introducing this abstraction. my main concern was with local models.
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.
That's a great opportunity for Apple to provide a universal unique model ID protocol and some shared storage space to allow devs to register models.
Do you guys not have phones (with at least 1TB of storage)?
Who’s “you guys” a developer from Bay Area? A student with a MacBook Neo? Or John Appleseed who bought basic iPhone 17e?
I have a Mac with 4TB of storage but it’s still annoying when every new AI app I try installs its own virtual environment with a fresh copy of Python, PyTorch, other duplicate libraries, and then models on top of that.
The apps can use the system provided on-device model using the same framework and APIs; but there's no affordances to deduplicate custom models between apps.
Is this Apple encouraging developers to go through their api abstraction layer to use LLMs so that when they launch their own (which I think we’ve heard they’ve been spending lots of money on training and might be somehow involved with Siri or current Apple AI?) that they can easily help devs make a seamless transition? Or is it just a developer nicety or something else?
Apple has some clever mechanics to protect user data. I had to work with App tracking stuff lately and their approach to keeping user details private with anonymized cohorts (SKAN, Differential Privacy) before reporting tracking events to third party platforms was surprisingly well thought out. There is value in having them in your loop if you care about privacy.
A dark, but not totally unfair take: It makes it easier for Apple to take payment for the models others provide, and even allows Apple, if they want to, to use the data to build a dataset for training their own models based on how users use third party models. It's only on Apple devices this API is used, so they split up the market by not letting developers use the same system if they want things to work on iOS, locking users even more in.
Call it Intelligence Store and charge… wait for it… 30%.
This is support for a new framework that ships with reality/mac/iPad/watch/tv/iOS 27 (and that they've promised to open-source later in the year, so presumably you'll also be able to lean on this if you ship Swift on your backend).
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.
The cynic (or realist?) in my thinks this abstraction layer is Apple's way of making sure that users give their own Apple Intelligence credit for the underlying LLM functionality, even if another company is actually providing the LLM.
Assembled in Cupertino once more. ;)
There are already on-device models that you can use through this framework as a developer. Claude would just be an additional one.
Maybe they plan to have the providers pay for being the default model? So basically, what Google is doing right now for search engines. The difference however is that Google is making money with additional search requests while AIs are (as of now) losing money with additional requests. I don't see the business case for them yet though.
> which I think we’ve heard they’ve been spending lots of money on training and might be somehow involved with Siri or current Apple AI
Lol bro this is literally it this is the model they've been training (was Apple Foundation model not a big enough hint?)
> Requests go directly from your app to the Claude API; Apple is not in the request path and does not see prompts or responses.
I know this is from a developer perspective. But as a consumer this is just funny.
From app developer standpoint why would anyone ship claude keys like that ... or am I missing something? From consumer standpoint - I guess they can use their own keys but it is not something that is very user friendly as you can imagine.
it says:
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...
Coding agent itself an imposed layer. Now they are adding one more layer? Many times I think of coding agent as the vendor supervisor from the body shops of the 90's who promise the customer everything under the sky and thrash the poor contractor to deliver. Coding agents consume 10x more tokens just like how body shops charged their customers vs how they paid the contractors. For a simple test, the same task that makes the model to go out of context length when used via a coding agent, runs fine when prompted directly.
Layers are luxury and remove control and transparency.
You wouldn't use this when building a coding agent.
the github repo: https://github.com/anthropics/ClaudeForFoundationModels
> Usage is billed to your Anthropic account at standard API pricing.
While expected, it’s still a bummer.
So where does the api key reside? You can’t ship it on the iOS client since anyone can read and abuse it
Misleading title. This is about Claude for Apple Foundation Models, not about Apple Foundation Models
Does "Apple Intelligence" need to be Turned On for this as well?
This seems smart. Apple, despite not really leading in AI themselves, are right on the hot path of where developers are going to yolo slop into the ecosystem. Make a tonne of sense to define a nice clean API that places like Anthropic can build on top of and expose to developers.
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%.
So actually the most successful AI was OpenRouter Intelligence? Pronounced as OÏ.
Why would I want a nerfed model?