The deployment target for my app was set to iOS 18.1 originally, but now that I'm using Foundational Models framework, it has been set to iOS 26.0. Is this ok?

I'm experimenting with downloading an audio file of spoken content, using the Speech framework to transcribe it, then using FoundationModels to clean up the formatting to add paragraph breaks and such. I have this code to do that cleanup: private func cleanupText(_ text: String) async throws -> String? { print("Cleaning up text of length \(text.count)...") let session = LanguageModelSession(instructions: "The content you read is a transcription of a speech. Separate it into paragraphs by adding newlines. Do not modify the content - only add newlines.") let response = try await session.respond(to: .init(text), generating: String.self) return response.content } The content length is about 29,000 characters. And I get this error: InferenceError::inferenceFailed::Failed to run inference: Context length of 4096 was exceeded during singleExtend.. Is 4096 a reference to a max input length? Or is this a bug? This is running on an M1 iPad Air, with iPadOS 26 Seed 1.

When I try to run visionOS 26 beta 2 on my device the app crashes on Launch: dyld[904]: Symbol not found: _$s16FoundationModels10TranscriptV7entriesACSayAC5EntryOG_tcfC Referenced from: <A71932DD-53EB-39E2-9733-32E9D961D186> /private/var/containers/Bundle/Application/53866099-99B1-4BBD-8C94-CD022646EB5D/VisionPets.app/VisionPets.debug.dylib Expected in: <F68A7984-6B48-3958-A48D-E9F541868C62> /System/Library/Frameworks/FoundationModels.framework/FoundationModels Symbol not found: _$s16FoundationModels10TranscriptV7entriesACSayAC5EntryOG_tcfC Referenced from: <A71932DD-53EB-39E2-9733-32E9D961D186> /private/var/containers/Bundle/Application/53866099-99B1-4BBD-8C94-CD022646EB5D/VisionPets.app/VisionPets.debug.dylib Expected in: <F68A7984-6B48-3958-A48D-E9F541868C62> /System/Library/Frameworks/FoundationModels.framework/FoundationModels dyld config: DYLD_LIBRARY_PATH=/usr/lib/system/introspection DYLD_INSERT_LIBRARIES=/usr/lib/libLogRedirect.dylib:/usr/lib/libBacktraceRecording.dylib:/usr/lib/libMainThreadChecker.dylib:/usr/lib/libViewDebuggerSupport.dylib:/System/Library/PrivateFrameworks/GPUToolsCapture.framework/GPUToolsCapture Symbol not found: _$s16FoundationModels10TranscriptV7entriesACSayAC5EntryOG_tcfC Referenced from: <A71932DD-53EB-39E2-9733-32E9D961D186> /private/var/containers/Bundle/Application/53866099-99B1-4BBD-8C94-CD022646EB5D/VisionPets.app/VisionPets.debug.dylib Expected in: <F68A7984-6B48-3958-A48D-E9F541868C62> /System/Library/Frameworks/FoundationModels.framework/FoundationModels dyld config: DYLD_LIBRARY_PATH=/usr/lib/system/introspection DYLD_INSERT_LIBRARIES=/usr/lib/libLogRedirect.dylib:/usr/lib/libBacktraceRecording.dylib:/usr/lib/libMainThreadChecker.dylib:/usr/lib/libViewDebuggerSupport.dylib:/System/Library/PrivateFrameworks/GPUToolsCapture.framework/GPUToolsCapture Message from debugger: Terminated due to signal 6

I am using Foundation Models for the first time and no response is being provided to me. Code import Playgrounds import FoundationModels #Playground { let session = LanguageModelSession() let result = try await session.respond(to: "List all the states in the USA") print(result.content) } Canvas Output What I did New file Code Canvas refreshes but nothing happens Am I missing a step or setup here? Please help. Something so basic is not working I do not know what to do. Running 40GPU, 16CPU MacBook Pro.. IOS26/Xcodebeta2/Tahoe allocated 8CPU, 48GB memory in Parallels VM. Settings for Playgrounds in Xcode Thank you for your help in advance.

Testing Foundation Models framework with a health-focused recipe generation app. The on-device approach is appealing but performance is rough. Taking 20+ seconds just to get recipe name and description. Same content from Claude API: 4 seconds. I know it's beta and on-device has different tradeoffs, but this is approaching unusable territory for real-time user experience. The streaming helps psychologically but doesn't mask the underlying latency.The privacy/cost benefits are compelling but not if users abandon the feature before it completes. Anyone else seeing similar performance? Is this expected for beta, or are there optimization techniques I'm missing?

Here's the result: Very weird.

Hi, I am a new IOS developer, trying to learn to integrate the Apple Foundation Model. my set up is: Mac M1 Pro MacOS 26 Beta Version 26.0 beta 3 Apple Intelligence &amp; Siri --&gt; On here is the code, func generate() { Task { isGenerating = true output = "⏳ Thinking..." do { let session = LanguageModelSession( instructions: """ Extract time from a message. Example Q: Golfing at 6PM A: 6PM """) let response = try await session.respond(to: "Go to gym at 7PM") output = response.content } catch { output = "❌ Error:, \(error)" print(output) } isGenerating = false } and I get these errors guardrailViolation(FoundationModels.LanguageModelSession.GenerationError.Context(debugDescription: "Prompt may contain sensitive or unsafe content", underlyingErrors: [Asset com.apple.gm.safety_embedding_deny.all not found in Model Catalog])) Can you help me get through this?

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?

I am working on an app using FoundationModels to process web pages. I am looking to find ways to filter the input to fit within the token limits. I have unit tests, UI tests and the app running on an iPad in the simulator. It appears that the different configurations of the test environment seems to affect the token limits. That is, the same input in a unit test and UI test will hit different token limits. Is this correct? Or is this an artifact of my test tooling?

Hey, I receive GenerableContent as follows: let response = try await session.respond(to: "", schema: generationSchema) And it wraps GeneratedJSON which seems to be private. What is the best way to get a string / raw value out of it? I noticed it could theoretically be accessed via transcriptEntries but it's not ideal.

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!

Hi all. My adapter model just won't invoke my tool. The problem I am having is covered in an older post: https://developer.apple.com/forums/thread/794839?answerId=852262022#852262022 Sadly the thread dies there and no resolution is seen in that thread. It's worth noting that I have developed an AI chatbot built around LanguageModelSession to which I feed the exact same system prompt that I feed to my training set (pasted further in this post). The AI chatbot works perfectly, the tool is invoked when needed. I am training the adapter model because the base model whilst capable doesn't produce the quality I'm looking for. So here's the template of an item in my training set: [ { 'role': 'system', 'content': systemPrompt, 'tools': [TOOL_DEFINITION] }, { 'role': 'user', 'content': entry['prompt'] }, { 'role': 'assistant', 'content': entry['code'] } ] where TOOL_DEFINITION = { 'type': 'function', 'function': { 'name': 'WriteUbersichtWidgetToFileSystem', 'description': 'Writes an Übersicht Widget to the file system. Call this tool as the last step in processing a prompt that generates a widget.', 'parameters': { 'type': 'object', 'properties': { 'jsxContent': { 'type': 'string', 'description': 'Complete JSX code for an Übersicht widget. This should include all required exports: command, refreshFrequency, render, and className. The JSX should be a complete, valid Übersicht widget file.' } }, 'required': ['jsxContent'] } } ... and systemPrompt = A conversation between a user and a helpful assistant. You are an Übersicht widget designer. Create Übersicht widgets when requested by the user. IMPORTANT: You have access to a tool called WriteUbersichtWidgetToFileSystem. When asked to create a widget, you MUST call this tool. ### Tool Usage: Call WriteUbersichtWidgetToFileSystem with complete JSX code that implements the Übersicht Widget API. Generate custom JSX based on the user's specific request - do not copy the example below. ### Übersicht Widget API (REQUIRED): Every Übersicht widget MUST export these 4 items: - export const command: The bash command to execute (string) - export const refreshFrequency: Refresh rate in milliseconds (number) - export const render: React component function that receives {output} prop (function) - export const className: CSS positioning for absolute placement (string) Example format (customize for each request): WriteUbersichtWidgetToFileSystem({jsxContent: `export const command = "echo hello"; export const refreshFrequency = 1000; export const render = ({output}) => { return <div>{output}</div>; }; export const className = "top: 20px; left: 20px;"`}) ### Rules: - The terms "ubersicht widget", "widget", "a widget", "the widget" must all be interpreted as "Übersicht widget" - Generate complete, valid JSX code that follows the Übersicht widget API - When you generate a widget, don't just show JSON or code - you MUST call the WriteUbersichtWidgetToFileSystem tool - Report the results to the user after calling the tool ### Examples: - "Generate a Übersicht widget" → Use WriteUbersichtWidgetToFileSystem tool - "Can you add a widget that shows the time" → Use WriteUbersichtWidgetToFileSystem tool - "Create a widget with a button" → Use WriteUbersichtWidgetToFileSystem tool When the script that I use to compose the full training set is executed, entry['prompt'] and entry['code'] contain the prompt and the resulting JSX code for one of the examples I'm feeding to the training session. This is repeated for about 60 such examples that I have in my sample data collection. Thanks for any help. Michael

Hi, I was using Foundation Models in my app, and suddenly it just stopped working from one moment to the next. To double-check, I created a small test in Playgrounds, but I’m getting the exact same error there too. #Playground { let session = LanguageModelSession() let prompt = "please answer a word" do { let response = try await session.respond(to: prompt) } catch { print("error is \(error)") } } error is Error Domain=FoundationModels.LanguageModelSession.GenerationError Code=-1 "(null)" UserInfo={NSMultipleUnderlyingErrorsKey=( "Error Domain=ModelManagerServices.ModelManagerError Code=1026 \"(null)\" UserInfo={NSMultipleUnderlyingErrorsKey=(\n)}" )} I’m no longer able to get any response from the framework anywhere, even in a fresh project. It's been 5 days. Has anyone else experienced this issue or knows what could be causing it? Thanks in advance! Tahoe 26.2 beta 1, Xcode 26.1.1, iPhone Air simulator 26.1

Hi all, I’m encountering an issue when trying to run Apple Foundation Models in a blank project targeting iOS 26. Below are the details: Xcode: Latest version with iOS 26 SDK macOS: macOS 26 Tahoe (installed on main disk) Mac: 16” MacBook Pro with M2 Pro chip Apple Intelligence: Available and functional on this machine Problem: I created a new blank iOS project, set the deployment target to iOS 26, and ran the following minimal code using Foundation Models. However, I get no response at all in the output - not even an error. The app runs, but the model does not produce any output. #Playground { let session = LanguageModelSession() let response = try await session.respond(to: "Tell me a story") } Then, I tried to catch an error with this code: #Playground { let session = LanguageModelSession() do { let response = try await session.respond(to: "Tell me a story") print(response) } catch { print("Failed to get response:", error) } print("This line, never gets executed") } And got these results: I’ve done further testing and discovered something important: I tried running the Code Along sample project, and there the #Playground macro worked without issues. The only significant difference I noticed was the Canvas run destination: In my original project, I was using iPhone 16 Pro (iOS 26) as the run target in Canvas. Apple Intelligence was enabled on the simulator, but no response was returned when executing the prompt. In the sample project, the Canvas was running on My Mac. I attempted to match that setup, but at first, my destination was My Mac (Designed for iPad), which still didn’t work. The macro finally executed properly once I switched to My Mac (AppKit). So the question is ... it seems that for now, Foundation Models and the #Playground macro only run correctly when the canvas or destination is set to “My Mac (AppKit)”?

Has Apple made any commitment to versioning the Foundation Models on device? What if you build a feature that works great on 26.0 but they change the model or guardrails in 26.1 and it breaks your feature, is your only recourse filing Feedback or pulling the feature from the app? Will there be a way to specify a model version like in all of the server based LLM provider APIs? If not, sounds risky to build on.

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.

I have a MacBook Pro M3 Pro with 18GB of RAM and was following the instructions to fine tune the foundational model given here: https://developer.apple.com/apple-intelligence/foundation-models-adapter/ However, while following the code sample in the example Jupyter notebook, my Mac hangs on the second code cell. Specifically: from examples.generate import generate_content, GenerationConfiguration from examples.data import Message output = generate_content( [[ Message.from_system("A conversation between a user and a helpful assistant. Taking the role as a play writer assistant for a kids' play."), Message.from_user("Write a script about penguins.") ]], GenerationConfiguration(temperature=0.0, max_new_tokens=128) ) output[0].response After some debugging, I was getting the following error: RuntimeError: MPS backend out of memory (MPS allocated: 22.64 GB, other allocations: 5.78 MB, max allowed: 22.64 GB). Tried to allocate 52.00 MB on private pool. Use PYTORCH_MPS_HIGH_WATERMARK_RATIO=0.0 to disable upper limit for memory allocations (may cause system failure). So is my machine not capable enough to adapter train Apple's Foundation Model? And if so, what's the recommended spec and could this be specified somewhere? Thanks!

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.

I am using macOS Tahoe on Xcode 26.

I'm experimenting with using the Foundation Models framework to do news summarization in an RSS app but I'm finding that a lot of articles are getting kicked back with a vague message about guardrails. This seems really common with political news but we're talking mainstream stuff, i.e. Politico, etc. If the models are this restrictive, this will be tough to use. Is this intended? FB17904424