Nvidia debuts $4,999 DGX Spark with half the RAM and storage, amid memory crunch
The cut-down model keeps the same GB10 chip and software stack while giving buyers a lower-cost option as memory prices climb, Nvidia said.
- Nvidia is expanding its DGX Spark personal AI supercomputer line with a new 64GB configuration, launching Friday, Oct. 23, exclusively through partners including Acer and Dell at $4,999.
- Skyrocketing memory costs forced Nvidia to raise the 128GB DGX Spark price to $6,950—nearly 75 percent higher than last year—necessitating this more affordable alternative for developers.
- Retaining the GB10 Grace Blackwell Superchip and 20-core MediaTek processor, the system allows users to run models with up to 100 billion parameters entirely on-device with no cloud dependency.
- Nvidia will release the NVIDIA Sync Model Launcher later this month to simplify cluster configurations, leveraging each unit's built-in ConnectX-7 network interface for seamless multi-device deployment.
- Competition is emerging from AMD's newly launched Gorgon Halo SoCs, which offer memory capacities ranging from around 32 GB to 192 GB for top-spec SKUs.
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NVIDIA declines its mini-supercomputer DGX Spark in a new version equipped with 64 GB of unified memory. Commercialized from 23 October at several manufacturers, it will be able to operate in pairs thanks to a new tool capable of automatically creating a local cluster.
NVIDIA opens a cheaper entrance door to its line of desk AI supercomputers. On October 2, 2026 the company presented a 64GB configuration of the NVIDIA DGX Spark AI system, the smallest and cheapest version of the original 128GB model, designed for those who want to run complex AI models without renting [...]
American semiconductor company Nvidia has introduced a slimmed-down version of its DGX Spark AI system with half the memory and storage to create an affordable alternative, British technology magazine The Register reports.
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Nvidia's new DGX Spark model could democratize AI supercomputing, but rising memory costs may challenge its affordability and market impact.
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