MLX Swift Bindings Let Developers Run Fine-Tuned LLMs on Apple Silicon Without CoreML

Developers can now load fine-tuned large language models directly on Apple Silicon using MLX Swift bindings, bypassing CoreML's compilation step entirely. CoreML typically requires 15–45 seconds of first-load compilation for a 3-billion-parameter model on M2, with each fine-tuning iteration triggering a new compilation cycle. MLX avoids this by using a lazy computation graph backed by Metal, taking advantage of the unified memory architecture found in M-series chips. The workflow involves converting model checkpoints to the .safetensors format using the mlx-lm Python toolchain, then loading them in Swift alongside KV-cache management via Swift 6 actors. Community benchmarks on M2 Pro suggest MLX outperforms CoreML's ANE pipeline for autoregressive text generation tasks, making it a practical choice for teams shipping frequent on-device model updates.