Running large AI models locally on resource-constrained devices without cloud dependency

Developers and Mac users want to run powerful large language models (26B+ parameters) on their personal devices with limited RAM (8-16GB) without relying on cloud APIs, but existing inference tools make this practically impossible due to memory constraints and prohibitive costs. Current solutions either require expensive cloud subscriptions, compromise on model capability, or demand high-end hardware that most users don't own.