For some reason feedbackassistant didn't work for me, so I'm uploading it here. https://1drv.ms/u/s!AmGvVvDPI0CMwTgzVGFESvcaAC2E?e=FcufOp This OneDrive folder contains the following contents ・Project Files ・sysdiagnoses ・Output of Xcode Here is what I wanted to write to FeedbackAssistant. Title : ANE in M1 max does not seem to be working. Xcode Version : Version 13.2.1 (13C100) Steps to reproduce : Run the project that exists at the URL presented earlier. That is all there is to the procedure. Note, the problem seems to occur only with M1 Pro , M1 Max.

I ran into this problem too. I used CoreML to do a simple image classification. I tested it on the following hardware. M1 Pro MacBook Pro 16 16G M1 iMac 24 16G intel MacBook Pro 13 16G iPhone 13 mini As a result of the verification, the following problems occurred only with M1Pro. H11ANEDevice::H11ANEDeviceOpen kH11ANEUserClientCommand_DeviceOpen call failed result=0xe00002bc Error opening LB - status=0xe00002bc.. Skipping LB and retrying So I also compared the execution speed and got the following results. M1 Pro(74s) M1 (52s) As shown above, the M1 was 42% faster than the M1Pro. My codes is like this: import Foundation import Vision import CoreML import CoreImage class MacInference{     private let model = try? testml(configuration: MLModelConfiguration()).model //CoreML model        var TopResultConfidence : Float = 0.0     var TopResultId = ""     var debug = false     private func checkFile(fileURL : String) -> Bool{         let filePath = fileURL.replacingOccurrences(of: "file://", with: "")         if FileManager.default.fileExists(atPath: filePath) {             return true         }else{             return false         }     }     func startML(fileURL : String){         let coreMLModel = try? VNCoreMLModel(for: self.model!)         let request = VNCoreMLRequest(model: coreMLModel!){ request, error in             if let results = request.results as? [VNClassificationObservation]{                 self.TopResultConfidence = results[0].confidence                 self.TopResultId = results[0].identifier                                  if self.debug {                     for result in results {                         print(result.confidence * 100, result.identifier)                     }                 }             }         }         if !self.checkFile(fileURL: fileURL){             print("URL error")             return         }         let ciimage = CIImage(contentsOf: URL(string: fileURL)!)         let handler = VNImageRequestHandler(ciImage: ciimage!, options: [:])         do {             try handler.perform([request])         } catch {             print(error)         }     } } let macML = MacInference() macML.debug = true macML.startML(fileURL: "FILE URL")