π Summary
Ultralytics v8.4.75 delivers an important CoreML reliability and speed fix for macOS πβ‘: CoreML models now run on Appleβs Neural Engine by default instead of using a setting that could crash Python processes on Mac hosts.
π Key Changes
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π Major CoreML backend fix for macOS
- The CoreML backend now loads models with
ComputeUnit.CPU_AND_NEinstead of the previous default behavior. - This avoids a known macOS
coremltoolsissue whereComputeUnit.ALLor GPU-enabled paths could trigger a hard crash withError: MLIR pass manager failed.
- The CoreML backend now loads models with
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β‘ 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.
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π‘οΈ Compatibility fallback for older macOS versions
- If
CPU_AND_NEis not supported, Ultralytics now falls back toCPU_ONLYrather than failing.
- If
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π Documentation updated
- The CoreML integration docs now explain the new macOS behavior and why avoiding the GPU path currently matters for stability.
π― Purpose & Impact
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π Fixes a serious usability issue for Mac users
- Before this release, running a CoreML
.mlpackagefrom Python on macOS could crash outright. - After this update, CoreML inference should work out of the box on supported Macs.
- Before this release, running a CoreML
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π 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.
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π§ 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.
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π₯ 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
.mlpackagemodels.
- Anyone using Ultralytics CoreML models from Python on a Mac benefits, especially those working with YOLO26 and other exported
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β 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 πβespecially 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 #24885
Full Changelog: v8.4.74...v8.4.75