GeeCoolGuest
GeeCoolA 7B-class quantized GGUF sits inside its reach. AVX-512 keeps llama.cpp's matrix kernels moving, 16 cores/32 threads soak up the parallelism, and dual-channel DDR5 paces the token stream. As a cardless fallback box, or a dedicated engine for corpus cleaning and embedding jobs, it is squarely in its element.
Paired with a discrete GPU it makes a clean data front-end. Keep the 128GB memory ceiling on the ledger: a 70B-class model cannot even be staged in RAM here, so that ambition belongs on a multi-channel platform or in the cloud. The modest iGPU means the machine still boots for debugging when the main card is out — that safety net costs you nothing.