The Chatterbox backend is pinned to the CPU on macOS, so voice cloning runs at
roughly 4x realtime there. This adds an MLX/Metal backend for the same engine and
selects it on Apple Silicon, mirroring the split the qwen engine already makes
between mlx_backend and pytorch_backend.
Measured on an M4 Max (36 GB) with a cloned pt-BR profile, same API, same profile,
model already loaded:
short sentence (1.8s of audio): 7.4-9.2s -> 1.2s
longer sentence (5.0s of audio): 23.7s -> 3.1s
The model config for chatterbox-tts is now backend aware, same as the qwen configs,
so the download matches the backend that will consume it.
Nothing changes off Apple Silicon: the PyTorch backend is still selected there, and
the CPU pinning it relies on is untouched.
