NVIDIA has announced two new personal AI supercomputers to handle AI workloads at the GPU Technology Conference (GTC) 2025 event. The company announced the DGX Spark and DGX Station, which are powered by the NVIDIA Grace Blackwell platform.
These are aimed at helping AI developers, researchers, data scientists, and even students prototype, fine-tune, and infer from large language models on a desktop. Models can be run locally or deployed on any cloud-based platform.
“DGX Spark and DGX Station bring the power of the Grace Blackwell architecture, previously only available in the data centre, to the desktop,” the company said. Original equipment manufacturer (OEM) partners like ASUS, Dell, HP and Lenovo are set to develop DGX Spark and the DGX Station.
The DGX Spark, formerly known as ‘Project DIGITS’, is dubbed the world’s smallest AI supercomputer. It can deliver 1,000 trillion operations per second (TOPS) using AI models. It is priced at $3,000. The NVIDIA DGX Spark (5.91″ × 5.91″ × 1.99″) is only slightly larger than the Apple Mac Mini (5.00″ × 5.00″ × 1.96″).
On the other hand, the more powerful NVIDIA DGX Station features a massive 784 GB memory to accelerate AI workloads. It is also the first desktop system built with the NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip. NVIDIA says the DGX Stations are purpose-built for teams who need the best desktop AI development platform.
“This is the computer of the age of AI. This is what computers should look like,” said CEO Jensen Huang in the keynote.
The company has opened reservations for DGX Spark Systems. The DGX Station is expected to be available later this year.
Besides, NVIDIA had plenty of announcements to make at the GTC event. The company also partnered with General Motors (GM) to develop AI-powered self-driving cars and HALOS, a new AI-enabled automotive safety platform. Furthermore, NVIDIA also announced plenty of updates in the robotics sector.
Earlier this year, the company unveiled the GeForce RTX 5090 GPU, which is 30% smaller in volume and 30% better at energy dissipation than the RTX 4090.
