Ollama Gets Blazing Fast on Macs with Full MLX Support and 2× Speedups

Ollama's latest update brings comprehensive MLX framework support to macOS, marking a significant milestone for Apple silicon-based local LLM deployment. The integration delivers up to 2× performance improvements compared to previous implementations and enables NVIDIA-quality 4-bit quantisation, making efficient inference accessible to Mac users without requiring external GPU acceleration.

This development is crucial for the local LLM community because it democratises high-performance inference on consumer Apple hardware. MLX's optimised kernels for Apple's Neural Engine now work seamlessly within Ollama's user-friendly interface, allowing practitioners to run larger models like Llama 2 70B or Mistral with substantially lower latency and memory footprint.

For developers and researchers, this means faster iteration cycles on MacBook Pros and iMacs, reduced dependency on cloud infrastructure, and better battery efficiency for edge deployment scenarios. The 4-bit quantisation parity with NVIDIA solutions removes a previous limitation where Mac users had to accept lower inference quality compared to CUDA deployments.

Source: QUASA Connect · Relevance: 9/10