🔗 Running local models on an M4 with 24GB memory

Experimenting with local models on an M4 with 24GB memory showcases the balance between convenience and performance. This article details the author's journey to find workable setups, emphasizing that while local models won't achieve the same results as state-of-the-art (SOTA) models, they provide an engaging alternative free from constant internet reliance.

The piece covers various model options like Qwen and configuration tweaks required for optimal function. Notably, Qwen 3.5-9B hits a sweet spot for performance, despite limitations such as becoming easily distracted. With deeper engagement required when using local models, the author argues that they can act as efficient research assistants while still offering room for error.

Ultimately, it highlights the fun of tinkering with these technologies and the appeal of a DIY approach in AI experimentation.