CoreML Optimizer

Expert guidance for optimizing machine learning models for Apple's CoreML framework on iOS and macOS devices.

When to Use This Skill

Use this skill when:

• Converting PyTorch/TensorFlow models to CoreML format
• Optimizing CoreML model size and inference latency
• Targeting the Neural Engine for maximum performance
• Debugging slow model inference or compute unit issues
• Applying quantization, palettization, or pruning
• Profiling model performance with Instruments
• Troubleshooting accuracy degradation after compression

Speed Optimization Checklist

The critical path to fast CoreML inference: