Ultralytics YOLO

🌟 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