NVIDIA RTX Spark laptops begin availability today, October 16, pairing an Arm CPU with Blackwell graphics and Windows 11. NVIDIA lists hundreds of supported games, including Fortnite, Counter-Strike 2 and Marvel Rivals. Call of Duty is explicitly scheduled for RTX Spark support in 2027.
Surface Laptop Ultra starts at a US MSRP of $2,599
Microsoft’s Surface Laptop Ultra announcement gives October 16 as the beginning of availability, with a $2,599 starting MSRP. Maximum configurations reach a 20-core CPU, a 6,144-core GPU and 128GB of unified memory. Those maximums do not describe every entry-level unit.
Shared CPU and GPU memory helps accommodate larger local AI workloads. Microsoft advertises support for models exceeding 120 billion parameters under applicable configurations, rather than guaranteeing every model at every precision. Our local versus cloud AI guide explains the infrastructure trade-off.
The 15-inch touchscreen laptop has removable storage and Magnetic Connect charging. Its included cable attaches magnetically to a USB-C port that remains usable for data and video.
Check individual games, including anti-cheat support
Arm compatibility includes a game’s components as well as its main executable. NVIDIA’s launch list includes ARC Raiders, Fortnite, Counter-Strike 2, Dota 2, Marvel Rivals, Rocket League, RUST and THE FINALS.
Call of Duty is a 2027 commitment, while Borderlands 4 is listed as coming soon. NVIDIA’s work with anti-cheat suppliers does not establish launch support for every game using one of those technologies.
RTX features still follow each game’s schedule
RTX Spark supports ray tracing, Reflex and DLSS, with NBA 2K27 receiving the faster DLSS 5 model on October 16. Hogwarts Legacy’s DLSS 5 update is scheduled for November 5. Those are game-specific integrations rather than automatic support across an installed library.
The ASUS ProArt RTX Spark systems previously demonstrated the platform’s local-AI and creative focus. Match the applications and games you need to the supported list before choosing a configuration by its maximum memory capacity.
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