Hello,
I have created this basic swift program:
let session = LanguageModelSession(
model: .default,
instructions: "bla bla bla.")
I want to understand what I can put in model parameter (instead of .default).
How can I choose between on-device local model (.default I suppose) and apple private cloud model (or any other ?)
Thanks
Foundation Models
RSS for tagDiscuss the Foundation Models framework which provides access to Apple’s on-device large language model that powers Apple Intelligence to help you perform intelligent tasks specific to your app.
Selecting any option will automatically load the page
Post
Replies
Boosts
Views
Activity
I have an app that streams in data from the Foundation Model and I have a card that shows one of the outputs. I want my card to accept a partially generated model but I keep getting a nonsensical error.
The error I get on line 59 is:
Cannot convert value of type 'FrostDate.VegetableSuggestion.PartiallyGenerated' (aka 'FrostDate.VegetableSuggestion') to expected argument type 'FrostDate.VegetableSuggestion.PartiallyGenerated'
Here is my card with preview:
import SwiftUI
import FoundationModels
struct VegetableSuggestionCard: View {
let vegetableSuggestion: VegetableSuggestion.PartiallyGenerated
init(vegetableSuggestion: VegetableSuggestion.PartiallyGenerated) {
self.vegetableSuggestion = vegetableSuggestion
}
var body: some View {
VStack(alignment: .leading, spacing: 8) {
if let name = vegetableSuggestion.vegetableName {
Text(name)
.font(.headline)
.frame(maxWidth: .infinity, alignment: .leading)
}
if let startIndoors = vegetableSuggestion.startSeedsIndoors {
Text("Start indoors: \(startIndoors)")
.frame(maxWidth: .infinity, alignment: .leading)
}
if let startOutdoors = vegetableSuggestion.startSeedsOutdoors {
Text("Start outdoors: \(startOutdoors)")
.frame(maxWidth: .infinity, alignment: .leading)
}
if let transplant = vegetableSuggestion.transplantSeedlingsOutdoors {
Text("Transplant: \(transplant)")
.frame(maxWidth: .infinity, alignment: .leading)
}
if let tips = vegetableSuggestion.tips {
Text("Tips: \(tips)")
.foregroundStyle(.secondary)
.frame(maxWidth: .infinity, alignment: .leading)
}
}
.padding(16)
.frame(maxWidth: .infinity, alignment: .leading)
.background(
RoundedRectangle(cornerRadius: 16, style: .continuous)
.fill(.background)
.overlay(
RoundedRectangle(cornerRadius: 16, style: .continuous)
.strokeBorder(.quaternary, lineWidth: 1)
)
.shadow(color: Color.black.opacity(0.05), radius: 6, x: 0, y: 2)
)
}
}
#Preview("Vegetable Suggestion Card") {
let sample = VegetableSuggestion.PartiallyGenerated(
vegetableName: "Tomato",
startSeedsIndoors: "6–8 weeks before last frost",
startSeedsOutdoors: "After last frost when soil is warm",
transplantSeedlingsOutdoors: "1–2 weeks after last frost",
tips: "Harden off seedlings; provide full sun and consistent moisture."
)
VegetableSuggestionCard(vegetableSuggestion: sample)
.padding()
.previewLayout(.sizeThatFits)
}
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Hi
For certain tasks, such as qualitative analysis or tagging, it is advisable to provide the AI with the option to respond with a joker / wild card answer when it encounters difficulties in tagging or scoring. For instance, you can include this slot in the prompt as follows:
output must be "not data to score" when there isn't information to score.
In the absence of these types of slots, AI trends to provide a solution even when there is insufficient information.
Foundations Models are told to be prompted with simple prompts. I wonder: Is recommended keep this slot though adds verbose complexity? Is the best place the comment of a guided attribute? other tips?
Another use case is when you want the AI to be tied to the information provided in the prompt and not take information from its data set. What is the best approach to this purpose?
Thanks in advance for any suggestion.
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Pretty much as per the title and I suspect I know the answer. Given that Foundation Models run on device, is it possible to use Foundation Models framework inside of a DeviceActivityReport? I've been tinkering with it, and all I get is errors and "Sandbox restrictions". Am I missing something? Seems like a missed trick to utilise on device AI/ML with other frameworks.
In working with Apple's foundation models, we often want to provide as much context as possible. However, since the model has a context size limit of 4096 tokens, is there a way to estimate the number of tokens beforehand?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
I want to use Foundation Models in a project, but I know my users will want to avoid environmentally intensive AI work in data centers.
Does Foundation Models ever use Private Compute Cloud or any other kind of cloud-based AI system?
I'd like to be able to assure my users that the LLM usage is relatively environmentally friendly. It would be great to be able to cite a specific Apple page explaining that Foundation Models work is always done locally.
If there's any chance that work can be done in the cloud, is there a way to opt out of that?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Hello, I was trying to test out Foundation Model however it says Model assets are unavailable. I got my MacBook M1 back in China when i was living there. is this due to region lock?
Hello
I’m experimenting with Apple’s on‑device language model via the FoundationModels framework in Xcode (using LanguageModelSession in my code). I’d like to confirm a few points:
• Is the language model provided by FoundationModels designed and trained by Apple? Or is it based on an open‑source model?
• Is this on‑device model available on iOS (and iPadOS), or is it limited to macOS?
• When I write code in Xcode, is code completion powered by this same local model? If so, why isn’t the same model available in the left‑hand chat sidebar in Xcode (so that I can use it there instead of relying on ChatGPT)?
• Can I grant this local model access to my personal data (photos, contacts, SMS, emails) so it can answer questions based on that information? If yes, what APIs, permission prompts, and privacy constraints apply?
Thanks
Hello,
I am studying macOS26 Apple Intelligence features.
I have created a basic swift program with Xcode. This program is sending prompts to FoundationModels.LanguageModelSession.
It works fine but this model is not trained for programming or code completion.
Xcode has an AI code completion feature. It is called "Predictive Code completion model".
So, there are multiple on-device models on macOS26 ?
Are there others ?
Is there a way for me to send prompts to this "Predictive Code completion model" from my program ?
Thanks
I would like to write a macOS application that uses on-device AI (FoundationModels).
I don’t understand how to, practically, give it access to my documents, photos, or contacts and be able to ask it a question like: “Find the document that talks about this topic.”
Do I need to manually retrieve the data and provide it in the form of a prompt? Or is FoundationModels capable of accessing it on its own?
Thanks
In this online session, you can code along with us as we build generative AI features into a sample app live in Xcode. We'll guide you through implementing core features like basic text generation, as well as advanced topics like guided generation for structured data output, streaming responses for dynamic UI updates, and tool calling to retrieve data or take an action.
Check out these resources to get started:
Download the project files: https://developer.apple.com/events/re...
Explore the code along guide: https://developer.apple.com/events/re...
Join the live Q&A: https://developer.apple.com/videos/pl...
Agenda – All times PDT
10 a.m.: Welcome and Xcode setup
10:15 a.m.: Framework basics, guided generation, and building prompts
11 a.m.: Break
11:10 a.m.: UI streaming, tool calling, and performance optimization
11:50 a.m.: Wrap up
All are welcome to attend the session. To actively code along, you'll need a Mac with Apple silicon that supports Apple Intelligence running the latest release of macOS Tahoe 26 and Xcode 26.
If you have questions after the code along concludes please share a post here in the forums and engage with the community.
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
I am excited to try Foundation Models during WWDC, but it doesn't work at all for me. When running on my iPad Pro M4 with iPadOS 26 seed 1, I get the following error even when running the simplest query:
let prompt = "How are you?"
let stream = session.streamResponse(to: prompt)
for try await partial in stream {
self.answer = partial
self.resultString = partial
}
In the Xcode console, I see the following error:
assetsUnavailable(FoundationModels.LanguageModelSession.GenerationError.Context(debugDescription: "Model is unavailable", underlyingErrors: []))
I have verified that Apple Intelligence is enabled on my iPad. Any tips on how can I get it working? I have also submitted this feedback: FB17896752
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Seeing this error from time to time:
Context(debugDescription: "Content contains 4089 tokens, which exceeds the maximum allowed context size of 4096.", underlyingErrors: [])
Of course, 4089 is less than 4096 so what is this telling me and how do I work around it? Is the limit actually lower than 4096?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Hey everyone,
Is it possible to generate XML using the “Generable” macro of the Foundation Model Framework?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Hi all, I am interested in unlocking unique applications with the new foundational models. I have a few questions regarding the availability of the following features:
Image Input: The update in June 2025 mentions "image" 44 times (https://machinelearning.apple.com/research/apple-foundation-models-2025-updates) - however I can't seem to find any information about having images as the input/prompt for the foundational models. When will this be available? I understand that there are existing Vision ML APIs, but I want image input into a multimodal on-device LLM (VLM) instead for features like "Which player is holding the ball in the image", etc (image understanding)
Cloud Foundational Model - when will this be available?
Thanks!
Clement :)
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Tags:
Vision
Machine Learning
Core ML
Apple Intelligence
Foundation Models are driving me up the wall.
My use case: A news app - I want to summarize news articles. Sounds like a perfect use for the added-in-beta-5 "no guardrails" mode for text-to-text transformations...
... and it's true, I don't get guardrails exceptions anymore but now, the model itself frequently refuses to summarize stuff which in a way is even worse as I have to parse the output text to figure out if it failed instead of getting an exception. I mostly worked that out with my system instructions but still, the refusing to summarize makes it really tough to use.
I instructed the model to tell me why it failed if that happens.
Examples of various refusals for news articles from major sources:
"The article mentions "Visual Lookup" but does not provide details about how it integrates with iOS 26."
"The article includes unsafe content regarding a political figure's potential influence over the Federal Reserve board, which is against my guidelines."
"the article contains unsafe content."
"The article is biased and opinionated and focuses on the author's opinion."
(this is despite the instructions specifically asking for a neutral summary - I am asking it to not use bias in the output but it still refuses)
I have tons of these. Note that if I don't use the "no guardrails" mode and use a Generable instead, some of these work fine so right now I have to do two passes on much of the content since I never know which one will work.
Having a "summary mode" that often refuses to summarize current news articles (the world is not a great place, some of these stories are a bummer) is near worthless.
Is the face and body detection service in the Vision framework a local model or a cloud model? Is there a performance report?
https://developer.apple.com/documentation/vision
Foundation Models framework worked perfectly on macOS 26 Beta 2, but starting from Beta 3 and continuing through Beta 6 (latest), I get dyld symbol errors even
with the exact code from Apple's documentation.
Environment:
macOS 26.0 Beta 6 (25A5351b)
Xcode 26 Beta 6
M4 Max MacBook Pro
Apple Intelligence enabled and downloaded
Error Details:
dyld[Process]: Symbol not found:
_$s16FoundationModels20LanguageModelSessionC5model10guardrails5tools12instructionsAcA06SystemcD0C_AC10GuardrailsVSayAA4Tool_pGAA12InstructionsVSgtcfC
Referenced from: /path/to/app.debug.dylib
Expected in: /System/Library/Frameworks/FoundationModels.framework/Versions/A/FoundationModels
Code Used (Exact from Documentation):
import FoundationModels
// This worked on Beta 2, crashes on Beta 3+
let model = SystemLanguageModel.default
let session = LanguageModelSession(model: model)
let response = try await session.respond(to: "Hello")
What I've Verified:
FoundationModels.framework exists in /System/Library/Frameworks/
Framework is properly linked in Xcode project
Apple Intelligence is enabled and working
Same code works in older beta versions
Issue persists even with completely fresh Xcode projects
Analysis:
The dyld error suggests the LanguageModelSession(model:) constructor is missing. The symbol shows it's looking for a constructor with parameters
(model:guardrails:tools:instructions:), but the documentation still shows the simple (model:) constructor.
Questions:
Has the LanguageModelSession API changed since Beta 2?
Should we now use the constructor with guardrails/tools/instructions parameters?
Is this a known issue with recent betas?
Are there updated code samples for the current API?
Additional Context:
This affects both basic SystemLanguageModel usage AND custom adapter loading. The same dyld symbol errors occur when trying to create
SystemLanguageModel(adapter: adapter) as well.
Any guidance on the correct API usage for current betas would be greatly appreciated. The documentation appears to be out of sync with the actual framework
implementation.
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
No matter what, the LanguageModelSession always returns very lengthy / verbose responses. I set the maximumResponseTokens option to various small numbers but it doesn't appear to have any effect. I've even used this instructions format to keep responses between 3-8 words but it returns multiple paragraphs. Is there a way to manage LLM response length? Thanks.
When the @Generable is applied toward a Swift struct declared within another struct, and when said nested struct is defined as the type of one of the properties of another @Generable type, which is in turn defined as the output format of Foundation Model session, Foundation Model can stuck in a loop trying to create a infinitely nested response, until the context window limit exceeded error is triggered.
I have filed feedback FB19987191 with a demo project. Is this expected behavior?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models