Good article about local LLM on MacBook Air (www.xda-developers.com)

Ollama has announced a significant upgrade to its MLX engine, which enhances the performance of local large language models (LLMs) on Apple Silicon-powered devices, particularly the MacBook Air. Users have reported nearly double the inference speed and increased responsiveness, even on machines with modest specifications like the MacBook Air M5 with 16GB of RAM. The MLX engine leverages Apple’s unified memory architecture and better handles GPU operations through a new just-in-time compiler, leading to a 20% improvement in output speed and more efficient memory usage during model inference. The update also introduces support for NVIDIA's NVFP4 quantization format, which significantly reduces memory usage without compromising output quality. This is crucial for users running smaller models on devices with limited resources, as it enables better performance and more coherent outputs in applications like code generation and automation. Additionally, the redesign of agent workflows allows for improved context management, making coding assistants more efficient by reducing redundant processing of unchanged context. Overall, these enhancements make Ollama's new MLX engine a meaningful upgrade for anyone using local LLMs on Apple Silicon systems.