One of the best tools for running AI models locally on Mac is now further improved. Here are the reasons and how to run it.

Local AI Models with Ollama Now Run Faster on Apple Silicon Macs

If you haven't met Ollama yet, it is an application for Mac, Linux, and Windows that allows users to run AI models locally on their computers.

Unlike cloud-based applications like ChatGPT, these models do not run locally and require an internet connection; Ollama allows users to load and run models directly on their machines.

These models can be downloaded from open-source communities like Hugging Face or directly from the model provider.

However, running LLMs locally can be quite challenging, as even small and lightweight LLMs tend to consume significant amounts of RAM and GPU memory.

To overcome this situation, Ollama has released a preview version of its application (Ollama 0.19), and this version is "now built on Apple’s machine learning framework MLX, enabling local AI models to run faster on Apple Silicon Macs by leveraging the unified memory architecture."

Here is Ollama:

This is causing a significant speed increase for Ollama on all Apple Silicon devices. On Apple’s M5, M5 Pro, and M5 Max chips, Ollama accelerates the time to first token (TTFT) and the production rate per token (tokens/second) by utilizing the new GPU Neural Accelerators.

With this update, Ollama states that running personal assistants like OpenClaw and coding agents such as “Claude Code, OpenCode, or Codex” is now faster.

However, Ollama recommends that users “please ensure you have a Mac with more than 32GB of unified memory,” which may not be feasible for many users wishing to run LLMs locally.

Still, you can follow this link to learn more about Ollama. If you want to learn more about Apple’s MLX project, you can find all the details here.

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