Wiring MLX and Core ML ANE Pipelines in Swift 6: On-Device Inference Without the Latency Cliff

How to structure concurrent Swift 6 actors around MLX's GPU compute and Core ML's ANE scheduler so inference requests never block the main actor, with concrete benchmarks on M-series chips showing when ANE outperforms GPU and vice versa for common mobile LLM workloads