Ollama's Apple Silicon Boost Makes Local AI Development More Practical

For developers exploring AI on their own hardware, a key tool just got a major upgrade. Ollama, a system for running large language models locally, now works with Apple's MLX framework. This integration, combined with enhanced caching and support for Nvidia's NVFP4 compression, is designed to unlock much faster performance on Macs with M-series chips.

The timing is significant. Interest in local models is moving beyond research labs, fueled partly by the viral attention around projects like OpenClaw. As developers encounter API costs and usage limits with cloud-based coding assistants, running models directly on a personal machine becomes a more attractive alternative for experimentation and specialized tasks.

Ollama's latest move caters directly to this shift. The capability is in preview with the 0.19 release, though it starts with support for a single, powerful model: the 35-billion-parameter Qwen3.5 from Alibaba. It demands serious hardware—an Apple Silicon Mac with at least 32GB of memory—highlighting that performant local AI remains a resource-intensive endeavor. This development, alongside recent improvements to its Visual Studio Code integration, signals Ollama's focus on smoothing the path for developers who want to bring AI workloads closer to home.

Source: Ars Technica