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
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.
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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
Hello,
I am testing the sample project provided here: Bringing advanced speech-to-text capabilities to your app.
On both macOS 26.0 beta and iOS 26.0 beta, the app crashes immediately on launch with a dyld "Symbol not found" error related to FoundationModels.framework.
It feels like this may be related to testing primarily on newer Apple Silicon devices, as I am seeing consistent crashes on an Intel MacBook and on an older iPhone device.
I would appreciate any insight, confirmation, or guidance on whether this is a known limitation or if there is a workaround. Is it planned to be resolved soon?
Environment
macOS:
Device: MacBook Pro (Intel)
Processor: 2 GHz Quad-Core Intel Core i5
Graphics: Intel Iris Plus Graphics 1536 MB
Memory: 16 GB 3733 MHz LPDDR4X
OS: macOS Tahoe Version 26.0 Beta (25A5338b)
iOS:
Device: iPhone 11
Model Number: MHDD3HN/A
OS: iOS 26.0
Xcode:
Version: 26.0 beta 3 (17A5276g)
Crash (macOS)
Abort signal received. Excerpt from crash dump:
dyld`__abort_with_payload:
0x7ff80e3ad4a0 <+0>: movl $0x2000209, %eax
0x7ff80e3ad4a5 <+5>: movq %rcx, %r10
0x7ff80e3ad4a8 <+8>: syscall
-> 0x7ff80e3ad4aa <+10>: jae 0x7ff80e3ad4b4
Console:
dyld[9819]: Symbol not found: _$s16FoundationModels20LanguageModelSessionC5model10guardrails5tools12instructionsAcA06SystemcD0C_AC10GuardrailsVSayAA4Tool_pGAA12InstructionsVSgtcfC
Referenced from: /Users/userx/Library/Developer/Xcode/DerivedData/SwiftTranscriptionSampleApp-*/Build/Products/Debug/SwiftTranscriptionSampleApp.app/Contents/MacOS/SwiftTranscriptionSampleApp.debug.dylib
Expected in: /System/Library/Frameworks/FoundationModels.framework/Versions/A/FoundationModels
Crash (iOS)
Abort signal received. Excerpt from crash dump:
dyld`__abort_with_payload:
0x18f22b4b0 <+0>: mov x16, #0x209
0x18f22b4b4 <+4>: svc #0x80
-> 0x18f22b4b8 <+8>: b.lo 0x18f22b4d8
Console
dyld[2080]: Symbol not found: _$s16FoundationModels20LanguageModelSessionC5model10guardrails5tools12instructionsAcA06SystemcD0C_AC10GuardrailsVSayAA4Tool_pGAA12InstructionsVSgtcfC
Referenced from: /private/var/containers/Bundle/Application/.../SwiftTranscriptionSampleApp.app/SwiftTranscriptionSampleApp.debug.dylib
Expected in: /System/Library/Frameworks/FoundationModels.framework/FoundationModels
Question
Is this crash expected on Intel Macs and older iPhone models with the beta SDKs?
Is there an official statement on whether macOS 26.x releases support Intel, or it exists only until macOS 26.1?
Any suggested workarounds for testing this sample project on current hardware?
Is this a known limitation for the 26.0 beta, and if so, should we expect a fix in 26.0 or only in subsequent releases?
Attaching screenshots for reference.
Thank you in advance.
I've tried creating a Lora adapter using the example dataset, scripts as part of the adapter_training_toolkit_v26_0_0 (last available) on MacOs 26 Beta 6.
import SwiftUI
import FoundationModels
import Playgrounds
#Playground {
// The absolute path to your adapter.
let localURL = URL(filePath: "/Users/syl/Downloads/adapter_training_toolkit_v26_0_0/train/test-lora.fmadapter")
// Initialize the adapter by using the local URL.
let adapter = try SystemLanguageModel.Adapter(fileURL: localURL)
// An instance of the the system language model using your adapter.
let customAdapterModel = SystemLanguageModel(adapter: adapter)
// Create a session and prompt the model.
let session = LanguageModelSession(model: customAdapterModel)
let response = try await session.respond(to: "hello")
}
I get Adapter assets are invalid error.
I've added the entitlements
Is adapter_training_toolkit_v26_0_0 up to date?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Hi,
Are there rules around using Foundation Models:
In a background task/session?
Concurrently, i.e. a bunch simultaneously using Swift Concurrency?
I couldn't find this in the docs (sorry if I missed it) so wondering what's supported and what the best practice is here.
In case it matters, my primary platform is Vision Pro (so, M2).
I have integrated Apple’s Foundation Model into my iOS application. As known, Foundation Model is only supported starting from iOS 26 on compatible devices. To maintain compatibility with older iOS versions, I wrapped the API calls with the condition if #available(iOS 26, *).
The application works normally on an iPad running iOS 18 and on a Mac running macOS 26. However, when running the same build on a MacBook Air M1 (macOS 15) through iPad app compatibility, the app crashes immediately upon launch.
The main issue is that I cannot debug directly on macOS 15, since the app can only be built on macOS 26 with Xcode beta. I then have to distribute it via TestFlight and download it on the MacBook Air M1 for testing. This makes identifying the detailed cause of the crash very difficult and time-consuming.
Nevertheless, I have confirmed that the crash is caused by the Foundation Model APIs.
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Problem:
We trained a LoRA adapter for Apple's FoundationModels framework using their TAMM (Training Adapter for Model Modification)
toolkit v0.2.0 on macOS 26 beta 4. The adapter trains successfully but fails to load with: "Adapter is not compatible with the
current system base model."
TAMM 2.0 contains export/constants.py with: BASE_SIGNATURE = "9799725ff8e851184037110b422d891ad3b92ec1"
Findings:
Adapter Export Process:
In export_fmadapter.py
def write_metadata(...):
self_dict[MetadataKeys.BASE_SIGNATURE] = BASE_SIGNATURE # Hardcoded value
The Compatibility Check:
- When loading an adapter, Apple's system compares the adapter's baseModelSignature with the current system model
- If they don't match: compatibleAdapterNotFound error
- The error doesn't reveal the expected signature
Questions:
- How is BASE_SIGNATURE derived from the base model?
- Is it SHA-1 of base-model.pt or some other computation?
- Can we compute the correct signature for beta 4?
- Or do we need Apple to release TAMM v0.3.0 with updated signature?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Tags:
Core ML
Create ML
tensorflow-metal
Apple Intelligence
Dear Apple Foundation Models Development Team,
I am a developer integrating Apple Foundation Models (AFM) into my app and encountered the exceededContextWindowSize error when exceeding the 4096-token limit.
Proposal:
I suggest Apple develop a tool to estimate the token count of a prompt before sending it to the model. This tool could be integrated into FoundationModels Framework for ease of use.
Benefits:
A token estimation tool would help developers manage the context window limit and optimize performance. I hope Apple considers this proposal soon.
Thank you!
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Was just wondering why the foundation model documentation is no longer available, thanks!
https://developer.apple.com/documentation/FoundationModels
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
I'm a bit new to the LLM stuff and with Foundation Models. My understanding is that there is a token limit of around 4K.
I want to process the contents of files which may be quite large. I first tried going the Tool route but that didn't work out so I then tried manually chunking the text to keep things under the limit.
It mostly works except that every now and then it'll exceed the limit. This happens even when the chunks are less than 100 characters. Instructions themselves are about 500 characters but still overall, well below 1000 characters per prompt, all told, which, in my limited understanding, should not result in 4K tokens being parsed.
Any ideas on what is going on here?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
I have a fairly basic prompt I've created that parses a list of locations out of a string. I've then created a tool, which for these locations, finds their latitude/longitude on a map and populates that in the response.
However, I cannot get the language model session to see/use my tool.
I have code like this passing the tool to my prompt:
class Parser {
func populate(locations: String, latitude: Double, longitude: Double) async {
let findLatLonTool = FindLatLonTool(latitude: latitude, longitude: longitude)
let session = LanguageModelSession(tools: [findLatLonTool]) {
"""
A prompt that populates a model with a list of locations.
"""
"""
Use the findLatLon tool to populate the latitude and longitude for the name of each location.
"""
}
let stream = session.streamResponse(to: "Parse these locations: \(locations)", generating: ParsedLocations.self)
let locationsModel = LocationsModels();
do {
for try await partialParsedLocations in stream {
locationsModel.parsedLocations = partialParsedLocations.content
}
} catch {
print("Error parsing")
}
}
}
And then the tool that looks something like this:
import Foundation
import FoundationModels
import MapKit
struct FindLatLonTool: Tool {
typealias Output = GeneratedContent
let name = "findLatLon"
let description = "Find the latitude / longitude of a location for a place name."
let latitude: Double
let longitude: Double
@Generable
struct Arguments {
@Guide(description: "This is the location name to look up.")
let locationName: String
}
func call(arguments: Arguments) async throws -> GeneratedContent {
let request = MKLocalSearch.Request()
request.naturalLanguageQuery = arguments.locationName
request.region = MKCoordinateRegion(
center: CLLocationCoordinate2D(latitude: latitude, longitude: longitude),
latitudinalMeters: 1_000_000,
longitudinalMeters: 1_000_000
)
let search = MKLocalSearch(request: request)
let coordinate = try await search.start().mapItems.first?.location.coordinate
if let coordinate = coordinate {
return GeneratedContent(
LatLonModel(latitude: coordinate.latitude, longitude: coordinate.longitude)
)
}
return GeneratedContent("Location was not found - no latitude / longitude is available.")
}
}
But trying a bunch of different prompts has not triggered the tool - instead, what appear to be totally random locations are filled in my resulting model and at no point does a breakpoint hit my tool code.
Has anybody successfully gotten a tool to be called?
I keep getting the error “An unsupported language or locale was used.”
Is there any documentation that specifies the accepted languages or locales in Foundation model?
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Hello,
My app fully relies on the new Foundation Models. Since Foundation Models require Apple Intelligence, I want to ensure that only devices capable of running Apple Intelligence can install my app.
When checking the UIRequiredDeviceCapabilities property for a suitable value, I found that iphone-performance-gaming-tier seems the closest match. Based on my research:
On iPhone, this effectively limits installation to iPhone 15 Pro or later.
On iPad, it ensures M1 or newer devices.
This exactly matches the hardware requirements for Apple Intelligence.
However, after setting iphone-performance-gaming-tier, I noticed that on iPad, Game Mode (Game Overlay) is automatically activated, and my app is treated as a game.
My questions are:
Is there a more appropriate UIRequiredDeviceCapabilities value that would enforce the same Apple Intelligence hardware requirements without triggering Game Mode?
If not, is there another way to restrict installation to devices meeting Apple Intelligence requirements?
Is there a way to prevent Game Mode from appearing for my app while still using this capability restriction?
Thanks in advance for your help.
We are really excited to have introduced the Foundation Models framework in WWDC25. When using the framework, you might have feedback about how it can better fit your use cases.
Starting in macOS/iOS 26 Beta 4, the best way to provide feedback is to use #Playground in Xcode. To do so:
In Xcode, create a playground using #Playground. Fore more information, see Running code snippets using the playground macro.
Reproduce the issue by setting up a session and generating a response with your prompt.
In the canvas on the right, click the thumbs-up icon to the right of the response.
Follow the instructions on the pop-up window and submit your feedback by clicking Share with Apple.
Another way to provide your feedback is to file a feedback report with relevant details. Specific to the Foundation Models framework, it’s super important to add the following information in your report:
Language model feedback
This feedback contains the session transcript, including the instructions, the prompts, the responses, etc. Without that, we can’t reason the model’s behavior, and hence can hardly take any action.
Use logFeedbackAttachment(sentiment:issues:desiredOutput: ) to retrieve the feedback data of your current model session, as shown in the usage example, write the data into a file, and then attach the file to your feedback report.
If you believe what you’d report is related to the system configuration, please capture a sysdiagnose and attach it to your feedback report as well.
The framework is still new. Your actionable feedback helps us evolve the framework quickly, and we appreciate that.
Thanks,
The Foundation Models framework team
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Whenever I try to initialize a LanguageModelSession (let session = LanguageModelSession()), my app crashes with EXC_BAD_ACCESS.
SystemLanguageModel.default.availability returns available.
I tried running the two sample projects I found that use Foundation Models, FoundationModelsTripPlanner and SwiftTranscriptionSampleApp, and they both also crash—immediately on launch.
I commented out the Foundation Models logic from the SwiftTranscriptionSampleApp and ran it again, and it no longer crashed.
I'm on macOS 26 Beta 4 on an M1 Pro device. I'm based in Austria (EU), if that matters.
Encountered a few times when the answer get "stuck" (I am now at beta 6).
This is an example.
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
Hi all,
I noticed on Friday that on the new Beta 5 using FoundationModels on a simulator LanguageModelSession.respond() neither resolves nor throws most of the time. The SwiftUI test app below was working perfectly in Xcode 16 Beta 4 and iOS 26 Beta 4 (simulator).
import SwiftUI
import FoundationModels
struct ContentView: View {
var body: some View {
VStack {
Image(systemName: "globe")
.imageScale(.large)
.foregroundStyle(.tint)
Text("Hello, world!")
}
.padding()
.onAppear {
Task {
do {
let session = LanguageModelSession()
let response = try await session.respond(to: "are cats better than dogs ???")
print(response.content)
} catch {
print("error")
}
}
}
}
}
After updating to Xcode 16 Beta 5 and iOS 26 Beta 5 (simulator), the code now often hangs.
Occasionally it will work if I toggle Apple Intelligence on and off in Settings, but it’s unreliable.
Topic:
Machine Learning & AI
SubTopic:
Foundation Models
I can no longer achieve 100% ANE usage since upgrading to MacOS26 Beta 5. I used to be able to get 100%. Has Apple activated throttling or power saving features in the new Betas? Is there any new rate limiting on the API? I can hardly get above 3w or 40%.
I have a M4 Pro mini (64GB) with High Power energy setting. MacOS 26 Beta 5.
Topic:
Machine Learning & AI
SubTopic:
Foundation Models