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

In the Foundation Models framework utilities package, the private method buildURLRequest in ChatCompletionsLanguageModel handles the construction of OpenAI-compatible API URLs: private func buildURLRequest(for request: ChatCompletionRequest) throws -> URLRequest { let isVersioned = baseURL.pathComponents.contains("v1") let endpoint = isVersioned ? "/chat/completions" : "/v1/chat/completions" let url = baseURL.appendingPathComponent(endpoint) ... } Problem The current implementation hardcodes "v1" to determine if the baseURL already includes a version. This limits compatibility with API providers using alternative versioning schemes. For instance, Volcengine Ark uses "v3" in its Base URL, making it difficult to seamlessly integrate their services. #Playground { let baseURL = URL(string: "https://ark.cn-beijing.volces.com/api/v3")! let modelName = "doubao-seed-2-0-mini-260428" let headers: [String : String] = [ "Authorization" : "Bearer \(apiKey)" ] let model = ChatCompletionsLanguageModel(name: modelName, url: baseURL, additionalHeaders: headers) let session = LanguageModelSession(model: model) do { let result = try await session.respond(to: "Hello").content } catch { print(error.localizedDescription) // HTTP error with status code 404: } } #Playground { let baseURL = URL(string: "https://ark.cn-beijing.volces.com/api/v3/responses")! let modelName = "doubao-seed-2-0-mini-260428" let headers: [String : String] = [ "Authorization" : "Bearer \(apiKey)" ] let model = ChatCompletionsLanguageModel(name: modelName, url: baseURL, additionalHeaders: headers) let session = LanguageModelSession(model: model) do { let result = try await session.respond(to: "Hello").content } catch { print(error.localizedDescription) /* HTTP error with status code 404: {"error":{"code":"InvalidAction","message":"The specified action is invalid: /api/v3/responses/v1/chat/completions Request id: 021784381168842fdfd2e3c33d5b6eddad55ac385080e727cab08","param":"","type":"NotFound"}} */ } } Suggested Solution To better accommodate different versioning conventions (e.g., v2, v3), we can leverage Swift's modern Regex (#/v\d+/#) to dynamically detect the version pattern in the path components. Here is a recommended update for the isVersioned check: let isVersioned = baseURL.pathComponents.contains { component in component.wholeMatch(of: #/v\d+/#) != nil }

Unless I'm missing something, it seems like the quota usage information for the Private Cloud Compute model is too limited. You can tell if you've reached your quota or are below it. If you are below your quota, you can tell if you're approaching the limit, but what does this actually mean? Am I over 50%, 90%, 99%? It would be nice to have actual numbers in the quota. For example, I can see my token usage for a session. If an app could keep track of that versus the quota, you could come up with something way more useful for the user. Example: You have 100,000 tokens per month, this app has made 4 requests, that used a total of 5,000 tokens. If the user has used on 95,000 tokens of their quota so far, they know they can maybe make ~4 more requests from the app before the limit is reached, so they know to be careful with their usage. If they've only used 10,000 tokens of their quota so far, they know that have some breathing room and can use the feature more freely. The way the current system is designed, you have no idea at all. Adding real numbers (even percentages – if we can get usage percentages for the app as well), would really help in giving useful feedback to the user on their usage of PCC. Right now, everything is too vague.

I had a great run in the first decade of iOS development. Not so much since. I had 180k downloaded units in the last year - but I'm excluded from foundation models because I did well before 2015. That seems like an odd policy. Apart from anything else - it explicitly punishes long-term accounts... Lifetime downloads...

During WWDC26 Keynote a second generation on-device model was announced with better speech generation capabilities. Is there a new API available for developers to generate speech?

Hello, I recently learned about Private Cloud Compute (PCC): https://developer.apple.com/private-cloud-compute/ I am currently using a standard Developer Program account, and it seems that I cannot apply for the program directly. Is there an alternative? Also, is there any additional fee for using this service? If I want to call PCC in the app, for example, using the following code: let session = LanguageModelSession( model: PrivateCloudComputeLanguageModel() ) Do I need to apply for a specific plan to ensure that my App is successfully published on the App Store and available to users? Thank you!

I am using the following code in my iOS application. #Playground { let session = LanguageModelSession() let response = try await session.respond(to: "List all states of USA.") print(response.content) } And I get the following error: The operation couldn’t be completed. (com.apple.SensitiveContentAnalysisML error 15.) I have turned off Apple Intelligence and turned on again. No use. I am using Xcode 27 beta 2. any ideas?

Hello. I have a problem with the FoundationModels adapter and the Apple-hosted managed asset pack via TestFlight. I have created an adapter that works fine locally by creating a model via (fileURL: URL) on a real device, but I cannot create a model using background assets by downloading the adapter via TestFlight. Every time I try to get an adapter, the creation of the adapter is interrupted by the compatibleAdapterNotFound error. The aar. archive i created using a special command - xcrun ba-package foundation-models package --adapter-path aurelius1.fmadapter --asset-pack-id fmadapter-aurelius1-9799725 --output-path ./aurelius1.aar --platforms iOS --on-demand\ after that, I replaced "OnDemand": null with "OnDemand": {} in the manifest so that the Transporter could send my archive to the App Store Connect. I followed all the recommendations in this topic - https://origin-devforums.apple.com/forums/thread/823148 ...but unfortunately unsuccessfully I would appreciate any help in solving this problem. here is the code that I use in my app -

Hello, I'm evaluating Foundation Models announced at WWDC 2026 and have a question regarding App Store distribution. My understanding is that Foundation Models are only available on supported devices and operating system versions. For apps that rely on Foundation Models as their primary functionality (rather than offering AI as an optional feature), I'm trying to understand the recommended distribution strategy. Currently, iOS provides Required Device Capabilities to prevent users from installing apps that require hardware features such as GPS, ARKit, or NFC. However, I couldn't find an equivalent Required Device Capability for Foundation Models. I also couldn't find a way to limit App Store availability by supported device models. My questions are: What is the recommended way to distribute an app whose primary functionality depends on Foundation Models? Is there currently any supported mechanism to prevent users with unsupported devices from downloading such an app? Is Apple planning to introduce a Required Device Capability (or a similar App Store filtering mechanism) for Foundation Models before public release? Without such a mechanism, users may be able to install the app successfully but then discover that its primary functionality is unavailable on their device. I'd appreciate any guidance on the recommended approach. Thank you.

I'm following along with the WWDC video on SpotlightSearchTool and hitting an error - looking for some guidance. I've configured SpotlightSearchTool and I'm sending it to the session. let session = LanguageModelSession(tools: [tool]) { spotlightSearchInstructions } let response = try await session.respond(to: prompt, options: GenerationOptions(toolCallingMode: .required)) I set the tool calling mode to required as a test - without it I don't get errors but the logging makes it seem like it's not calling the search tool and the responses would seem to confirm that (they're not grounded in my data). So, I figured I'd try forcing it to use the tool. When I do that, I get this console error: InferenceError::hostFailed::InferenceError::inferenceFailed::TokenGenerationCore.GuidedGenerationError.invalidConfiguration(errorMessage: "Tool Choice requires tools") in response to ExecuteRequest Error during session.respond. description="The operation couldn’t be completed. (FoundationModels.LanguageModelError error -1.)" Returning empty Spotlight result. elapsedMs=3254 toolReplies=0 totalSearchItems=0 uniqueSearchItems=0 What does that mean? I'm passing in a tool, everything compiles correctly, etc. Not sure how to debug - any advice appreciated! Testing this via the Simulator on beta 3.

Since beta 2 I think, it seems Foundation models are not accessible if Siri AI is not enabled. I'm on Mac OS, and not sure how it works on iOS, but does that mean that Foundation Models will not be usable if Siri AI is not enabled (Europe)?

I have a health app on the App Store that uses Foundation Models to generate brief narrative summaries from the user's own glucose and menstrual cycle data. No medical advice, just supportive summaries of their own numbers. This has been working reliably on iOS 26.x since early 2026. After updating to iOS 27 beta 2, every prompt is refused. The error is LanguageModelError ("The model refused to answer" / "May contain sensitive content"), not GenerationError.guardrailViolation. I've confirmed: Same device, same code, same prompts. Worked on iOS 26.x, fails on iOS 27 beta 2. Two independent features with different prompt structures and different service architectures are both affected. Using SystemLanguageModel(guardrails: .permissiveContentTransformations) does not help. The classifier passes. The model itself refuses. The prompts contain terms like "luteal phase," "progesterone," "glucose," "time in range," and "diabetes" in the system instructions. This appears to be a model-level sensitivity change in the iOS 27 on-device model that broadly blocks health/medical terminology, even when the use case is summarizing the user's own data. Filed as FB23513774 with the full prompt text, instructions, and source file attached. Is anyone else seeing model-level refusals (not guardrailViolation) on iOS 27 beta for health or medical content? Related threads from iOS 26 betas: Model Guardrails Too Restrictive? Model w/ Guardrails Disabled Still Refusing Using Past Versions of Foundation Models As They Progress

Apologies, if I've missed the answer already here, I've searched around but can't find it. Foundation models and Private Cloud Compute require Apple Intelligence to be enabled in Settings as mentioned here. At the same time it says that Foundation Models PCC calls are supported on all Apple Watch models that run WatchOS 27. So, will there be a seperate Apple Intelligence setting in WatchOS 27 for those devices? Otherwise if a user has an Apple Watch Series 11 (which does support Apple Intelligence) paired with an iPhone 15 (which doesn't support Apple Intelligence), will they be unable to use the Foundation Models PCC calls from WatchOS in my app? Despite the fact the iPhone isn't involved in these queries anyway?

On this talk: Bring an LLM provider to the Foundation Models framework URL: https://developer.apple.com/videos/play/wwdc2026/339/ on the coding examples a very peculiar framework is shown: import MLXFoundationModels However I am not able to find it nowhere, there is even a code section with this framework as part of an example. Where is this framework, there are no BETA branches on the MLX framework either. Thanks!

When importing FoundationModels in watchOS 27 Beta 2 this error appears: /Applications/Xcode-beta.app/Contents/Developer/Platforms/WatchOS.platform/Developer/SDKs/WatchOS27.0.sdk/System/Library/Frameworks/FoundationModels.framework/Modules/FoundationModels.swiftmodule/arm64e-apple-watchos.swiftinterface:6:15 Unable to resolve module dependency: 'CoreImage' Does anybody else have this issue?

I’ve been experimenting with Foundation Models and built a small Swift package that wraps LanguageModelSession with simple context management. The current approach checks the transcript token count using tokenCount(for:), compacts the transcript when it reaches a threshold, and retries once if exceededContextWindowSize is thrown. I’d appreciate feedback on whether this is a sensible use of Foundation Models APIs, especially around rebuilding a session from a compacted Transcript. GitHub: https://github.com/ricky-stone/FoundationContext

I have an app on the App Store that takes user content and creates a Generable struct out of it. In the last couple weeks I have started getting complains from my users that the part of the app leveraging FoundationModels isn't working properly. In my testing I noticed that the same request that would've worked a couple weeks ago is now getting errors with guardrails violation. I'm initializing my model this way LanguageModelSession(model: SystemLanguageModel(guardrails: .permissiveContentTransformations)) // I'm aware that .permissiveContentTransformations does not apply to Generable, but I'd really really really really love it, if it did!. This started around the iOS 26.5/macOS 26.5 releases and I wonder if there's a way to fix it.

Hi Apple Team, I'm trying to use the SkillActivation framework from the Foundation Models Utilities repository: https://github.com/apple/foundation-models-utilities Environment: Xcode 26 Beta iPadOS/macOS 26 Beta Apple Intelligence enabled Foundation Models Utilities: latest version from GitHub Issue: As soon as I import or use SkillActivation-related APIs, Xcode reports build errors and the project fails to compile. The rest of the Foundation Models framework works correctly, but the problem appears specifically when SkillActivation is added. Steps to Reproduce: Create a new project. Add foundation-models-utilities via Swift Package Manager. Import SkillActivation / follow the sample implementation. Build the project. Expected Result: The project should compile successfully and SkillActivation should be available. Actual Result: Xcode reports compilation errors and the build fails. Questions: Is there any additional entitlement, capability, or configuration required for SkillActivation? Is SkillActivation currently supported in Xcode 26 Beta? Are there any known issues with the current version of foundation-models-utilities? Thank you.

On iOS 27 Beta 1, it looks like the user must enable either "Siri"/"Hey Siri" or "Press Side Button for Siri" in iOS settings for SystemLanguageModel.default.availability to report true. Otherwise, it returns .appleIntelligenceNotEnabled. Is this expected behavior? This doesn't seem very intuitive. The user might very well want to use in-app AI functionalities without wanting to talk / press side button for Siri. Also, with the new "pull down for Siri" UX these are not the only way to interact with Siri anyway.

In the new Xcode we saw examples of Claude, OAI & Google coding agents that you can start conversations with inside your project, giving it access to your project files context. As far as I understand, this requires an API key for those models & the processing is run on Anthropic / Google servers, not locally nor on Private Cloud Compute. Is it possible to instead, use the LLM powering Foundation Models, for a “Siri Code Agent” which operates in the place of those models, but runs on device or in Private Cloud Compute? I like how this works for Siri AI requests, and would love to have a coding assistant agent that can operate in the same privacy preserving way! Is this possible with any of the open source frameworks or the command line tools? If not, what is the best way to request this feature?

Whisper and other STT APIs let you pass a custom vocabulary or initial_prompt to bias recognition toward domain-specific proper nouns. In the App Intents / Siri stack, is there an equivalent way to supply dynamic, per-user term lists — for example favorites or recently used items — to improve how spoken names are transcribed or resolved?