pypi ultralytics 8.4.75
v8.4.75 - Run CoreML on the Neural Engine (CPU_AND_NE) on macOS hosts (#24885)

4 hours ago

🌟 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.

πŸ“Š Key Changes

  • πŸš‘ 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.
  • πŸ›‘οΈ Compatibility fallback for older macOS versions

    • If CPU_AND_NE is not supported, Ultralytics now falls back to CPU_ONLY rather than failing.
  • πŸ“ 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.
  • πŸš€ Improves inference speed

    • The reported result shows about 2.5 ms on the Neural Engine vs 8.5 ms on CPU, roughly a 3Γ— speedup.
    • This is especially valuable for real-time or interactive applications.
  • πŸ”§ 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.
  • πŸ‘₯ 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.
  • βœ… 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 πŸŽ‰β€”especially for macOS users running CoreML models locally, where it turns a crash-prone path into a fast, working default.

What's Changed

Full Changelog: v8.4.74...v8.4.75

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