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Nvidia's Grace Blackwell superchips are officially coming to the PC with RTX Spark notebooks
COMPUTEX 2026: It only took a year and a half but the same silicon at the heart of Nvidia's DGX Spark AI workstations will soon be powering Windows PCs. During his GTC Taiwan keynote on Monday, Nvidia CEO Jensen Huang revealed the N1X, a high-end mobile processor that combines an Arm-based CPU co-designed with MediaTek with a Blackwell based GPU on board. Marketed under the “RTX Spark” banner, Nvidia’s new notebooks and mini PCs signal a deeper push into the a PC arena long dominated by...
NVIDIA's RTX Spark is an AI "superchip" that will power Windows laptops and desktops
NVIDIA's RTX Spark is an AI "superchip" that will power Windows laptops and desktops The company claims it offers 1 petaflop of AI computing power. It was only a matter of time before NVIDIA released a powerful system-on-a-chip (SOC) to take on AMD's Ryzen AI Max and Qualcomm's latest Snapdragon X2 chips. At Computex today, NVIDIA unveiled the RTX Spark, a "superchip" meant to give both laptops and small desktops fast AI and graphics performance.
Our systems editor flew all the way to Taiwan and still couldn't get away from AI
KETTLE El Reg's systems editor Tobias Mann has been in Taipei for the past week getting the skinny on the hottest new chips, and what he's heard has been less about actual hardware announcements and more about how chipmakers are rushing to meet the demands of AI, other customers be damned. Tobias joins host Brandon Vigliarolo to discuss what he noticed at Computex 2026, how AI has taken over yet another industry event, and whether the world is going to have to adjust to new, more expensive...
Nvidia’s RTX Spark Laptops Look Hell-Bent on Disruption
The moment many have been waiting years for has arrived. Nvidia has long made graphics cards that powered the Windows PC ecosystem for decades—now it wants to control the whole thing with “superchips,” starting with the RTX Spark. Announced over the weekend at the Computex tech expo in Taiwan, RTX Spark chips combine unified memory, RTX graphics, and the new part: the N1 CPU.
Nvidia announces RTX Spark as ‘the most efficient PC chip ever built’
This fall, Nvidia will officially become a consumer PC chipmaker like Intel, AMD, Apple, and Qualcomm, putting a complete computing chip - not just graphics - into the very heart of laptops and mini-PCs. After many months of leaks, it's finally announcing the RTX Spark, the first in a family of chips that will meet or beat the most powerful thin-and-light Windows machines ever, it claims. "This is the most efficient PC chip ever built," says Nvidia senior director of product management Mark...
NVIDIA's RTX Spark chip could give Windows its true Apple Silicon moment
NVIDIA's RTX Spark chip could give Windows its true Apple Silicon moment Arm CPU cores, a powerful GPU and gobs of unified RAM? That sounds familiar! There's a lot we still don't know about NVIDIA's RTX Spark AI chip — we're still waiting on deeper technical details and pricing for the first batch of systems — but it has a decent shot of changing the way we think of Windows PCs entirely.
I Put a Datacenter GPU in My Gaming PC for £200
I Put a Datacenter GPU in My Gaming PC for £200 I already had an RTX 4080. Good enough for gaming, not good enough for the models I wanted to run locally. The next step up in GPU land is either spend a fortune on a card with more VRAM, or find another way.
The Morning After: NVIDIA thinks its new chip will revolutionize PCs
The Morning After: NVIDIA thinks its new chip will revolutionize PCs Plus, NASA ends a Mars mission and Meta’s still being creepy. It's been a busy week, with Computex and Microsoft Build just two of the raft of big events going on right now.
Parallelizing Large-Scale Tensor Network Contraction on Multiple GPUs
arXiv:2606.01852v1 Announce Type: new Abstract: Exact tensor network contraction underpins quantum circuit simulation, quantum error correction, combinatorial optimization, and many-body dynamics. The dominant parallelization strategy, slicing, scales exponentially and incurs redundant computation. We present a multi-GPU framework that instead distributes intermediate tensors across devices with explicit communication, converting a fixed contraction path into a communication-efficient...