Every Way to Get 192GB for Local AI (Without a $9,500 Mac)

The author evaluates several alternative hardware configurations for running local AI models at the 192GB memory tier without purchasing an expensive Mac Studio. Testing reveals significant performance bottlenecks, including memory splitting overheads across multiple GPUs and hidden context memory requirements such as KV cache that constrain practical capacity. Ultimately, the analysis demonstrates that many popular hardware builds face severe software and architectural limitations that prevent them from matching their specifications in real-world usage. Open article →