I'm playing with the new Vision API for iOS18, specifically with the new CalculateImageAestheticsScoresRequest API. When I try to perform the image observation request I get this error: internalError("Error Domain=NSOSStatusErrorDomain Code=-1 \"Failed to create espresso context.\" UserInfo={NSLocalizedDescription=Failed to create espresso context.}") The code is pretty straightforward: if let image = image { let request = CalculateImageAestheticsScoresRequest() Task { do { let cgImg = image.cgImage! let observations = try await request.perform(on: cgImg) let description = observations.description let score = observations.overallScore print(description) print(score) } catch { print(error) } } } I'm running it on a M2 using the simulator. Is it a bug? What's wrong?

I found what might be a bug with enabling Apple Intelligence when switching languages. When my iPhone's language is set to Catalan, the Apple Intelligence is disabled because it is not available for that language. Switching to Spanish doesn't activate it, and it still shows the same message of being unavailable, this time saying not available in Spanish (which is not true). However, it is enabled when the phone is rebooted. Once at this point, the bug becomes even weirder. Having the iPhone language set to Spanish and with Apple Intelligence on, I switch the language to Catalan, and the feature remains enabled. After I ask a query in Catalan, it surprisingly understands it and works, but then it gets disabled. Apart from that, as user feedback, I would love to activate Apple Intelligence in an available language other than my device's language. That's how I always used Siri (iPhone in Catalan, Siri in Spanish). Thanks!

Lookin for J - is this a safe place for discussing full apps ive built but not submitted or shared , I have maybe over 100 but had been unaware any assistance was provided.. is there a formal process to take to submit an app fro review to improve OS, other than during App Store review.

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.

I am using the iPhone 17 Pro simulator that was included with Xcode 26.0.1. My Mac is running macOS 26. When I started the simulator for the first time I got the "Ready for Apple Intelligence" notification but when I access Image Playground in my app it says it is not available on this iPhone. Any solution to get it working on the simulator?

Hello everyone, I have a visual convolutional model and a video that has been decoded into many frames. When I perform inference on each frame in a loop, the speed is a bit slow. So, I started 4 threads, each running inference simultaneously, but I found that the speed is the same as serial inference, every single forward inference is slower. I used the mactop tool to check the GPU utilization, and it was only around 20%. Is this normal? How can I accelerate it?

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

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?

I just recently updated to iOS 26 beta (23A5336a) to test an app I am developing I running an MLModel loaded from a .mlmodelc file. On the current iOS version 18.6.2 the model is running as expected with no issues. However on iOS 26 I am now getting error when trying to perform an inference to the model where I pass a camera frame into it. Below is the error I am seeing when I attempt to run an inference. at the bottom it says "Failed with status=0x1d : statusType=0x9: Program Inference error status=-1 Unable to compute the prediction using a neural network model. It can be an invalid input data or broken/unsupported model " does this indicate I need to convert my model or something? I don't understand since it runs as normal on iOS 18. Any help getting this to run again would be greatly appreciated. Thank you, processRequest:model:qos:qIndex:modelStringID:options:returnValue:error:: Could not process request ret=0x1d lModel=_ANEModel: { modelURL=file:///var/containers/Bundle/Application/04F01BF5-D48B-44EC-A5F6-3C7389CF4856/RizzCanvas.app/faceParsing.mlmodelc/ : sourceURL=(null) : UUID=46228BFC-19B0-45BF-B18D-4A2942EEC144 : key={"isegment":0,"inputs":{"input":{"shape":[512,512,1,3,1]}},"outputs":{"var_633":{"shape":[512,512,1,19,1]},"94_argmax_out_value":{"shape":[512,512,1,1,1]},"argmax_out":{"shape":[512,512,1,1,1]},"var_637":{"shape":[512,512,1,19,1]}}} : identifierSource=1 : cacheURLIdentifier=01EF2D3DDB9BA8FD1FDE18C7CCDABA1D78C6BD02DC421D37D4E4A9D34B9F8181_93D03B87030C23427646D13E326EC55368695C3F61B2D32264CFC33E02FFD9FF : string_id=0x00000000 : program=_ANEProgramForEvaluation: { programHandle=259022032430 : intermediateBufferHandle=13949 : queueDepth=127 } : state=3 : [Espresso::ANERuntimeEngine::__forward_segment 0] evaluate[RealTime]WithModel returned 0; code=8 err=Error Domain=com.apple.appleneuralengine Code=8 "processRequest:model:qos:qIndex:modelStringID:options:returnValue:error:: ANEProgramProcessRequestDirect() Failed with status=0x1d : statusType=0x9: Program Inference error" UserInfo={NSLocalizedDescription=processRequest:model:qos:qIndex:modelStringID:options:returnValue:error:: ANEProgramProcessRequestDirect() Failed with status=0x1d : statusType=0x9: Program Inference error} [Espresso::handle_ex_plan] exception=Espresso exception: "Generic error": ANEF error: /private/var/containers/Bundle/Application/04F01BF5-D48B-44EC-A5F6-3C7389CF4856/RizzCanvas.app/faceParsing.mlmodelc/model.espresso.net, processRequest:model:qos:qIndex:modelStringID:options:returnValue:error:: ANEProgramProcessRequestDirect() Failed with status=0x1d : statusType=0x9: Program Inference error status=-1 Unable to compute the prediction using a neural network model. It can be an invalid input data or broken/unsupported model (error code: -1). Error Domain=com.apple.Vision Code=3 "The VNCoreMLTransform request failed" UserInfo={NSLocalizedDescription=The VNCoreMLTransform request failed, NSUnderlyingError=0x114d92940 {Error Domain=com.apple.CoreML Code=0 "Unable to compute the prediction using a neural network model. It can be an invalid input data or broken/unsupported model (error code: -1)." UserInfo={NSLocalizedDescription=Unable to compute the prediction using a neural network model. It can be an invalid input data or broken/unsupported model (error code: -1).}}}

The developer tutorial for visual intelligence indicates that the method to detect and handle taps on a displayed entity from the Search section is via an "OpenIntent" associated with your entity. However, running this intent executes code from within my app. If I have the perform() method display UI, it always displays UI from within my app. I noticed that the Google app's integration to visual intelligence has a different behavior-- tapping on an entity does not take you to the Google app -- instead, a Webview is presented sheet-style WITHIN the Visual Intelligence environment (see below) How is that accomplished?

Hardware: Macbook Pro M4 Nov 2024 Software: macOS Tahoe 26.0 & xcode 26.0 Apple Intelligence is activated and the Image playground macOS app works Running the following on xcode throws ImagePlayground.ImageCreator.Error.creationFailed Any suggestions on how to make this work? import Foundation import ImagePlayground Task { let creator = try await ImageCreator() guard let style = creator.availableStyles.first else { print("No styles available") exit(1) } let images = creator.images( for: [.text("A cat wearing mittens.")], style: style, limit: 1) for try await image in images { print("Generated image: \(image)") } exit(0) } RunLoop.main.run()

Is the face and body detection service in the Vision framework a local model or a cloud model? https://developer.apple.com/documentation/vision

I’m working on generating images using Image Playground. The code works fine for other styles but fails when using an external provider. I don’t see any other requirements mentioned in the documentation. Has anyone else encountered a similar issue? Here’s the relevant code snippet: https://developer.apple.com/documentation/imageplayground/imageplaygroundstyle/externalprovider?changes=_2 The error message is also not very helpful. It simply states that the creation failed. Note: I have enabled ChatGPT Plus, and the image generation using ChatGPT styles works fine when using the Playground app. do { let creator = try await ImageCreator() let concept = ImagePlaygroundConcept.text("Love") let images = creator.images(for: [concept], style: .externalProvider, limit: 1) for try await image in images { // Handle image break } } catch { // Handle error } I’m using the iOS 26 RC, and when I print creator.availableStyles, it doesn’t display the external Provider. [ImagePlayground.ImagePlaygroundStyle(id: "animation", _representationInfo: nil), ImagePlayground.ImagePlaygroundStyle(id: "emoji", _representationInfo: nil), ImagePlayground.ImagePlaygroundStyle(id: "illustration", _representationInfo: nil), ImagePlayground.ImagePlaygroundStyle(id: "sketch", _representationInfo: nil), ImagePlayground.ImagePlaygroundStyle(id: "messages-background", _representationInfo: nil)]

Hey everyone, Is it possible to generate XML using the “Generable” macro of the Foundation Model Framework?

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 :)

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.

I'm adding Visual Intelligence support to my app, and now want to add a Tip using TipKit to guide users to this feature from within my app. I want to add a Rule to my Tip which will only show this Tip on devices where Visual Intelligence is supported (ex. not iPhone 14 Pro Max). What is the best way for me to determine availability to set this TipKit rule? Here's the documentation I'm following for Visual Intelligence: https://developer.apple.com/documentation/visualintelligence/integrating-your-app-with-visual-intelligence

Are there any guidelines for using Foundation Models To generate text for users in response to some canned queries? Should we use a special icon or text to let the user know that Apple Intelligence is generating the text? Should there be a disclaimer like, Apple Intelligence can make mistakes, please check for accuracy, etc?