🌟 Summary Ultralytics v8.4.75 delivers an important CoreML reliability and speed fix for macOS 🍎⚡: CoreML models now run on Apple's Neural Engine by default instead of using a setting that could crash Python processes on Mac hosts. 📊 Key Changes 🚑 Major CoreML backend fix for macOS The CoreML backend now loads models with ComputeUnit.CPU_AND_NE instead of the previous default behavior. This avoids a known macOS coremltools issue where ComputeUnit.ALL or GPU-enabled paths could trigger a hard crash with Error: MLIR pass manager failed. ⚡ Neural Engine enabled by default on supported Macs On macOS 13 and newer, CoreML inference now uses the CPU + Neural Engine path automatically. This gives much better performance than CPU-only execution. 🛡️ Compatibility fallback for older macOS versions If CPU_AND_NE is not supported, Ultralytics now falls back to CPU_ONLY rather than failing. 📝 Documentation updated The CoreML integration docs now explain the new macOS behavior and why avoiding the GPU path currently matters for stability. 🎯 Purpose & Impact 🍏 Fixes a serious usability issue for Mac users Before this release, running a CoreML .mlpackage from Python on macOS could crash outright. After this update, CoreML inference should work out of the box on supported Macs. 🚀 Improves inference speed The reported result shows about 2.5 ms on the Neural Engine vs 8.5 ms on CPU, roughly a 3× speedup. This is especially valuable for real-time or interactive applications. 🔧 Makes CoreML deployment more dependable Users exporting YOLO models to CoreML for local Mac inference should see a much smoother experience with fewer platform-specific failures. 👥 Broad impact for Python users on Apple Silicon Anyone using Ultralytics CoreML models from Python on a Mac benefits, especially those working with YOLO26 and other exported .mlpackage models. ✅ No major new model architecture changes This release is mainly a backend stability and performance update, not a new model release. The biggest win is that existing CoreML workflows on macOS should now be both faster and far more reliable. In short: v8.4.75 is a small but high-impact release 🎉—especially for macOS users running CoreML models locally, where it turns a crash-prone path into a fast, working default. What's Changed Run CoreML on the Neural Engine (CPU_AND_NE) on macOS hosts by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/24885 Full Changelog: https://github.com/ultralytics/ultralytics/compare/v8.4.74...v8.4.75