Hi, I’m testing Unity’s Spaceship HDRP demo on iPhone 17 Pro Max and iPad Pro M4 (iOS 26.1). Everything renders correctly, and my custom MetalFX Spatial plugin initializes successfully — it briefly reports active scaling (e.g. 1434×660 → 2868×1320 at 50% scaling), then reverts to native rendering a few frames later. Setup: Xcode 16.1 (targeting iOS 18) Unity 2022.3.62f3 (HDRP) Metal backend Dynamic Resolution enabled in HDRP assets and cameras Relevant Xcode console excerpt: [MetalFXPlugin] MetalFX_Enable(True) called. [SpaceshipOptions] MetalFX enabled with HDRP dynamic resolution integration. [SpaceshipOptions] Disabled TAA for MetalFX Spatial. [SpaceshipOptions] Created runtime RenderTexture: 1434x660 [MetalFX] Spatial scaler created (1434x660 → 2868x1320). [MetalFX] Processed frame with scaler. [MetalFXPlugin] Sent RenderTexture (1434x660) to MetalFX. Output target 2868x1320. [SpaceshipOptions] MetalFX target set: 1434x660 [SpaceshipOptions] Camera targetTexture cleared after MetalFX handoff. It looks like HDRP clears the camera’s target texture right after MetalFX submits the frame, which causes it to revert to native rendering. Is there a recommended way to persist or rebind the MetalFX output texture when using HDRP on iOS? Unity doesn’t appear to support MetalFX in the Editor either: Thanks!

Hi, I'm Beginner with Metal 4 and Model I/O 🥺. I can render simple models with just one mesh, but when I try to render models with SubMeshes, nothing shows up on screen. Can anyone help me figure out how to properly render models with multiple submeshes? I think I'm not iterating through them correctly or maybe missing some buffers setup. Here's what I have so far: https://www.icloud.com.cn/iclouddrive/0a6x_NLwlWy-herPocExZ8g3Q#LoadModel

After watching WWDC 2025 session "Combine Metal 4 machine learning and graphics", I have decided to give it a shot to integrate the latest MTL4MachineLearningCommandEncoder to my existing render pipeline. After a lot of trial and errors, I managed to set up the pipeline and have the app compiled. However, I am now stuck on creating a MTLLibrary with .mtlpackage. Here is the code I have to create a MTLLibrary according the WWDC session https://developer.apple.com/videos/play/wwdc2025/262/?time=550: let coreMLFilePath = bundle.path(forResource: "my_model", ofType: "mtlpackage")! let coreMLURL = URL(string: coreMLFilePath)! do { metalDevice.makeLibrary(URL: coreMLURL) } catch { print("error: \(error)") } With the above code, I am getting error: Error Domain=MTLLibraryErrorDomain Code=1 "Invalid metal package" UserInfo={NSLocalizedDescription=Invalid metal package} What is the correct way to create a MTLLibrary with .mtlpackage? Do I see this error because the .mtlpackage I am using is incorrect? How should I go with debugging this? I'd really appreciate if I could get some help on this as I have been stuck with it for some time now. Thanks in advance!

Hello, I recently watched the WWDC2025 session titled “Combine Metal 4 machine learning and graphics” (https://developer.apple.com/videos/play/wwdc2025/262/ ), and I’m very excited about the new Metal 4 features that integrate machine learning with graphics—such as neural ambient occlusion, shader-based ML inference, and the use of MTLTensor and MTL4MachineLearningCommandEncoder. While the session includes helpful code snippets and a compelling debug demo (e.g., the neural ambient occlusion example), the implementation details are not fully shown, and I haven’t been able to find a complete, runnable sample project that demonstrates end-to-end integration of ML and rendering in Metal 4. Would Apple be able to provide a full, working example—such as an Xcode project—that shows how to: Export a model to an .mlpackage, Convert it to an .mtlpackage, Use MTL4MachineLearningCommandEncoder alongside render passes, Or embed small neural networks directly in shaders using Shader ML? Having such a sample would greatly help developers like me adopt these powerful new capabilities correctly and efficiently. Thank you very much for your time and support! Best regards,

The following minimal snippet SEGFAULTS with SDK 26.0 and 26.1. Won't crash if I remove async from the enclosing function signature - but it's impractical in a real project. import Metal import MetalPerformanceShaders let SEED = UInt64(0x0) typealias T = Float16 /* Why ran in async context? Because global GPU object, and async makeMTLFunction, and async makeMTLComputePipelineState. Nevertheless, can trigger the bug without using global @MainActor let myGPU = MyGPU() */ @main struct CMDLine { static func main() async { let ptr = UnsafeMutablePointer<T>.allocate(capacity: 0) async let future: Void = randomFillOnGPU(ptr, count: 0) print("Main thread is playing around") await future print("Successfully reached the end.") } static func randomFillOnGPU(_ buf: UnsafeMutablePointer<T>, count destbufcount: Int) async { // let (device, queue) = await (myGPU.device, myGPU.commandqueue) let myGPU = MyGPU() let (device, queue) = (myGPU.device, myGPU.commandqueue) // Init MTLBuffer, async let makeFunction, makeComputePipelineState, etc. let tempDataType = MPSDataType.uInt32 let randfiller = MPSMatrixRandomMTGP32(device: device, destinationDataType: tempDataType, seed: Int(bitPattern:UInt(SEED))) print("randomFillOnGPU: successfully created MPSMatrixRandom.") // try await computePipelineState // ^ Crashes before this could return // Or in this minimal case, after randomFillOnGPU() returns // make encoder, set pso, dispatch, commit... } } actor MyGPU { let device : MTLDevice let commandqueue : MTLCommandQueue init() { guard let dev: MTLDevice = MPSGetPreferredDevice(.skipRemovable), let cq = dev.makeCommandQueue(), dev.supportsFamily(.apple6) || dev.supportsFamily(.mac2) else { print("Unable to get Metal Device! Exiting"); exit(EX_UNAVAILABLE) } print("Selected device: \(String(format: "%llX", dev.registryID))") self.device = dev self.commandqueue = cq print("myGPU: initialization complete.") } } See FB20916929. Apparently objc autorelease pool is releasing the wrong address during context switch (across suspension points). I wonder why such obvious case has not been caught before.

I have a Core Image filter in my app that uses Metal. I cannot compile it because it complains that the executable tool metal is not available, but I have installed it in Xcode. If I go to the "Components" section of Xcode Settings, it shows it as downloaded. And if I run the suggested command, it also shows it as installed. Any advice? Xcode Version Version 26.0 beta (17A5241e) Build Output Showing All Errors Only Build target Lessons of project StudyJapanese with configuration Light RuleScriptExecution /Users/chris/Library/Developer/Xcode/DerivedData/StudyJapanese-glbneyedpsgxhscqueifpekwaofk/Build/Intermediates.noindex/StudyJapanese.build/Light-iphonesimulator/Lessons.build/DerivedSources/OtsuThresholdKernel.ci.air /Users/chris/Code/SerpentiSei/Shared/iOS/CoreImage/OtsuThresholdKernel.ci.metal normal undefined_arch (in target 'Lessons' from project 'StudyJapanese') cd /Users/chris/Code/SerpentiSei/StudyJapanese /bin/sh -c xcrun\ metal\ -w\ -c\ -fcikernel\ \"\$\{INPUT_FILE_PATH\}\"\ -o\ \"\$\{SCRIPT_OUTPUT_FILE_0\}\"' ' error: error: cannot execute tool 'metal' due to missing Metal Toolchain; use: xcodebuild -downloadComponent MetalToolchain /Users/chris/Code/SerpentiSei/StudyJapanese/error:1:1: cannot execute tool 'metal' due to missing Metal Toolchain; use: xcodebuild -downloadComponent MetalToolchain Build failed 6/9/25, 8:31 PM 27.1 seconds Result of xcodebuild -downloadComponent MetalToolchain (after switching Xcode-beta.app with xcode-select) xcodebuild -downloadComponent MetalToolchain Beginning asset download... Downloaded asset to: /System/Library/AssetsV2/com_apple_MobileAsset_MetalToolchain/4d77809b60771042e514cfcf39662c6d1c195f7d.asset/AssetData/Restore/022-19457-035.dmg Done downloading: Metal Toolchain (17A5241c). Screenshots from Xcode Result of "Copy Information" Metal Toolchain 26.0 [com.apple.MobileAsset.MetalToolchain: 17.0 (17A5241c)] (Installed)

Hi everyone, This project uses PyTorch on an Apple Silicon Mac (M1/M2/etc.), and the goal is to use the MPS backend for GPU acceleration, notes Apple Developer. However, the workflow depends on Float64 (double-precision) floating-point numbers for certain computations, notes PyTorch Forums. The error "Cannot convert a MPS Tensor to float64 dtype as the MPS framework doesn't support float64. Please use float32 instead" has been encountered, notes GitHub. It seems that the MPS backend doesn't currently support Float64 for direct GPU computation. Questions for the community: Are there any known workarounds or best practices for handling Float64-dependent operations when using the MPS backend with PyTorch? For those working with high-precision tasks on Apple Silicon, what strategies are being used to balance performance with the need for Float64? Offloading to the CPU is an option, and it's of interest to know if there are any specific techniques or libraries within the Apple ecosystem that could streamline this process while aiming for optimal performance. Any insights, tips, or experiences would be appreciated. Thanks in advance, Jonaid MacBook Pro M3 Max

Context I’m deploying large language models on iPhone using llama.cpp. A new iPhone Air (12 GB RAM) reports a Metal MTLDevice.recommendedMaxWorkingSetSize of 8,192 MB, and my attempt to load Llama-2-13B Q4_K (~7.32 GB weights) fails during model initialization. Environment Device: iPhone Air (12 GB RAM) iOS: 26 Xcode: 26.0.1 Build: Metal backend enabled llama.cpp App runs on device (not Simulator) What I’m seeing MTLCreateSystemDefaultDevice().recommendedMaxWorkingSetSize == 8192 MiB Loading Llama-2-13B Q4_K (7.32 GB) fails to complete. Logs indicate memory pressure / allocation issues consistent with the 8 GB working-set guidance. Smaller models (e.g., 7B/8B with similar quantization) load and run (8B Q4_K provide around 9 tokens/second decoding speed). Questions Is 8,192 MB an expected recommendedMaxWorkingSetSize on a 12 GB iPhone? What values should I expect on other 2025 devices including iPhone 17 (8 GB RAM) and iPhone 17 Pro (12 GB RAM) Is it strictly enforced by Metal allocations (heaps/buffers), or advisory for best performance/eviction behavior? Can a process practically exceed this for long-lived buffers without immediate Jetsam risk? Any guidance for LLM scenarios near the limit?

subj And how in this case are beautiful system dials made with smoke effects and other particles?

I am trying to learn the new Metal Peformance Primitives APIs. I have added the MetalPeformancePrimitives framework and included the header in my shader code as per documentation #include <MetalPeformancePrimitives/MetalPeformancePrimitives.h> Unfortunately, Xcode complains that the header cannot be found. How do I include it properly? I am using Xcode 26 on Tahoe. The MetalPeformancePrimitives framework is present on my machine and I can inspect the headers in the filesystem.

Hello, I am quite new to using the metal API and was wondering if it was common (or even possible) if you knew that, when a pipeline was created, you never needed to make another one with the same shaders again, if it is safe to release the library the was used to reference the shaders? Only asking because this is possible in other apis, but apple never mentions (as far as I have found) if this is safe or not safe to do.

I'm updating our app to support metal 4, but the metal 4 types don't seem to get recognized when targeting simulator. Is it known if metal 4 will be supported in the near future, or am I setting up the app wrong?

Hi, I’m using the latest iPad Pro (13-inch) and I can see that Metal offers an rgb10a2unorm texture for rendering, but when I render a grey ramp and measure the actual luminance, I get a pattern that I would expect from an 8-bit texture (see below). Before I start ripping apart all my code, is there anything else I need to do to convince iOS to render my texture in 10-bit? I already tried setting the PixelFormat in my CMetalLayer to rgb10a2unorm, but that didn’t change anything.

Hello, Shaders in our application is written using HLSL and we rely on Metal Shader Converter to convert DXIL to Metal IR. We ran into an issue that causes metal pipeline state creation to fail when vertex stage-in function is used on AMD GPUs. Here's the error reported by Metal in Xcode output: Compiler failed with XPC_ERROR_CONNECTION_INTERRUPTED XPC_ERROR_CONNECTION_INTERRUPTED MTLCompiler: Compilation failed with XPC_ERROR_CONNECTION_INTERRUPTED on 4 try. This error suggests an unexpected interruption in the connection. Possible reasons: a crash in the compiler service, termination by the OS due to resource constraints (e.g., jetsam), a timeout in the service, or an issue with IPC. Verify system stability and check the logs for more details. Compiler failed with XPC_ERROR_CONNECTION_INVALID XPC_ERROR_CONNECTION_INVALID MTLCompiler: Compiler encountered XPC_ERROR_CONNECTION_INVALID: failed to check-in, peer may have been unloaded: mach_error=10000003 (is the OS shutting down or process jetsammed?) Compilation failed due to an interrupted connection: XPC_ERROR_CONNECTION_INTERRUPTED. This error occurred after multiple retries. which seems to indicate a internal compiler error. I have a minimal repro here: https://github.com/kcloudy0717/metal_pso_fail/tree/main, simply follow the instructions in README.

I rewrote my graphics pipeline to use Load/Store better for clearing and don't care cases. All my tests pass, and in the Metal debugger, all the draw calls succeed. But when I present drawables (before [commandBuffer commit]) I only get a pink screen. I've tried everything I can think of: making sure the pixel formats are the same for the back buffer as my render targets, etc. But it's still pink. Could you point me in the right direction so I can fix this, or help describe why it's pink. That would be really helpful. Thank you, Brian Hapgood

Can't seem to get the Metal HUD to display value range's (pre 26 Tahoe). The documented environment variable MTL_HUD_SHOW_VALUE_RANGE doesn't seem to work. https://developer.apple.com/documentation/xcode/monitoring-your-metal-apps-graphics-performance#Display-the-value-range-of-metrics Anyone having any luck?

Just wondering if anyone knows what it will take to hit greater than 60hz when targeting iPhone. If I set the preferredFramesPerSecond of an MTKView to 120, it works on the iPad, but on iPhone it never goes over 60hz, even with a simple hello triangle sample app... is this a limitation of targeting iPhone?

We set the CVDisplayLink on macOS to 0 or 120, and get the following. This then clamps maximum refresh to 60Hz on the 120Hz ProMotion display on a MBP M2 Max laptop. How is this not fixed in 4 macOS releases? CoreVideo: currentVBLDelta returned 200000 for display 1 -- ignoring unreasonable value CoreVideo: [0x7fe2fb816020] Bad CurrentVBLDelta for display 1 is zero. defaulting to 60Hz.

I have really enjoyed looking through the code and videos related to Metal 4. Currently, my interest is to update a ReSTIR Project and take advantage of more robust ways to refit acceleration Structures and more powerful ways to access resources. I am working in Swift and have encountered a couple of puzzles: What is the 'accepted' way to create a MTL4BufferRange to store indices and vertices? How do I properly rewrite Swift code to build and compact an Acceleration Structure? I do realize that this is all in Beta and will happily look through Code Samples this Fall. If other guidance is available earlier, that would be fabulous! Thank you

I mean…I want to use defaults rather than launching apps via open with the saved environment variables. This is pretty easy on iOS and other platforms. So what about in macOS?