My AI lab in a box {or} how I foresee the AI Desktop Future
Copyright: Sanjay Basu I am running llama.cpp on NVIDIA DGX Spark The NVIDIA DGX Spark just made desktop AI supercomputing accessible. This compact mini PC delivers 1 petaflop of AI performance with 128GB of unified memory . Enough to run models up to 200 billion parameters locally using llama.cpp. It’s bringing data center capabilities to my desk, and the implications are profound for anyone serious about local AI development. Why does this matter? Because for the first time, developers, researchers, and enterprises can fine-tune 70B parameter models and run inference on 200B parameter models entirely on their desks, without data center dependencies, API costs, or data leaving their infrastructure. The DGX Spark paired with llama.cpp’s optimized inference engine creates a sweet spot. Powerful enough for serious work, accessible enough for individuals, and private enough for sensitive applications. While memory bandwidth at 273 GB/s creates some trade-offs compared to discr...