Nvidia RTX Spark Laptops Launch with Prices up to $7,000 Targeting High-End Creators

Image: The Verge · Source

Nvidia's new RTX Spark-powered laptops are now available from brands including Dell, Asus, and Microsoft, featuring high-end configurations priced from $2,599 to nearly $7,000, aiming to compete with premium MacBook Pros among creators and AI users.

Nvidia has introduced its new generation of laptops powered by the RTX Spark chip, featuring models from major OEMs like Dell, Lenovo, MSI, HP, Asus, and Microsoft. These devices, designed to appeal to creative professionals and local AI workloads, come with price tags reflecting their premium specifications. The base configurations start around $2,599, including an 18-core CPU, 24GB of unified memory, and 512GB of storage, positioning them against similarly sized MacBook Pros with Apple’s M5 Pro chip, which offers 1TB of storage for a comparable price.

At the high end, configurations escalate significantly. The Asus ProArt P16, equipped with a 20-core CPU, 128GB of unified memory, and 2TB of storage, commands a price of up to $6,999.99. Meanwhile, Microsoft's Surface Laptop Ultra, still with limited configuration details publicly available, is listed in a 48GB RAM variant at $3,999.99 via Best Buy. Full pricing options for the Surface Laptop Ultra remain forthcoming.

Such steep pricing is not unprecedented in the premium laptop segment, particularly with Apple’s MacBook Pro models which can approach nearly $10,000 when fully configured with an M5 Max chip. Nvidia’s RTX Spark laptops reflect a strategic focus on creators requiring powerful computation and AI capabilities locally, where expanded unified memory and processing cores justify the higher costs amid prevailing market conditions that have driven memory prices up.

These RTX Spark laptops are launching this month, with availability starting as early as October 16, 2026. Reviews and user reports will shed light on how well these models perform relative to their premium pricing and Apple’s offerings in terms of real-world creative workloads and AI tasks.