Nvidia has boldly entered a new segment of the rapidly growing AI market by creating its own “supercomputer” that fits on a desktop. The new device, called DGX Spark, costs $4,000 and comes equipped with 128 GB of unified memory shared between the CPU and GPU — allowing it to run models with up to 200 billion parameters locally, without relying on cloud infrastructure.
With DGX Spark, Nvidia aims to “democratize” AI computing power, targeting users who need high-performance local processing without maintaining costly server setups. It also addresses the growing demand for local AI models that don’t require sending sensitive data to the cloud — an increasingly important factor in terms of privacy and security.
The size is another selling point — DGX Spark takes up about as much desk space as a file binder (it’s a 2.65-pound box measuring 5.91 x 5.91 x 1.99 inches). Despite its power, it draws only 240 watts, making it a highly energy-efficient solution compared to full-size AI workstations.
DGX Spark Specifications:
- GPU: NVIDIA Blackwell Architecture with 5th Generation Tensor Cores and 4th Generation RT Cores
- CPU: 20-core Arm processor (10 Cortex-X925 + 10 Cortex-A725)
- Memory: 128 GB LPDDR5x unified memory, 256-bit interface, 4266 MHz, 273 GB/s bandwidth
- Storage: 1 TB or 4 TB NVMe M.2 with self-encryption
- Network: 1x RJ-45 (10 GbE), ConnectX-7 Smart NIC, Wi-Fi 7, Bluetooth 5.4
- Connectivity: 4x USB Type-C, 1x HDMI 2.1a, multichannel HDMI audio
- Video Processing: 1x NVENC, 1x NVDEC
The system is designed to empower researchers, startups, and R&D teams to experiment with large generative AI models locally, without having to invest in traditional high-end workstations that often cost over $10,000.
Nvidia is also encouraging OEM partners – including Dell, Asus, HP, and Lenovo – to develop their own versions of the DGX Spark, helping accelerate the growth of the compact AI hardware ecosystem.
