Nvidia CEO Jensen Huang says the company’s new laptop platform delivers 1 petaflop of AI performance. That’s a figure that used to describe machines filling entire rooms.
Now it fits in a backpack. The pitch is simple: run serious AI models on your own device instead of renting someone else’s servers.
What Nvidia actually built
The hardware is called RTX Spark, and its centerpiece is what Nvidia calls a “superchip.” It pairs a Blackwell RTX GPU with a Grace CPU that Nvidia designed in collaboration with MediaTek.
On paper, the specs are hefty. The GPU carries up to 6,144 CUDA cores, the parallel processors that do the heavy math for graphics and AI. The CPU side brings 20 cores.
The headline number comes with a footnote. The platform hits up to 1 petaflop of FP4 AI performance.
FP4 refers to 4-bit floating point, a compact number format that trades some precision for speed. It’s popular for running AI models efficiently, but it’s not the same as raw, high-precision compute.
Memory might be the more important spec. RTX Spark offers up to 128GB of unified LPDDR5X memory, shared between the CPU and GPU rather than split into separate pools.
Nvidia says the setup can run large language models with up to 120 billion parameters locally on a Windows laptop.
Who’s selling it, and for how much
Nvidia isn’t building the laptops itself. Machines from ASUS, Dell, HP, Lenovo, Microsoft, and MSI became available on October 16, 2026.
Pricing starts at $2,599. Top-tier configurations are expected to sell between $3,000 and $7,000.
Nvidia is aiming at three crowds at once: creators, developers, and gamers.
For gamers, Nvidia says the platform handles AAA titles at 1440p resolution with frame rates above 100 fps. For creators, it claims support for 12K video editing and 3D rendering while running on battery power.
The Arm question
RTX Spark runs on an Arm-based architecture, not the x86 design that has powered most Windows PCs for decades.
Microsoft has optimized Windows 11 for this Arm-based setup. It also includes emulation for legacy x86 applications, meaning older software built for traditional PCs can still run.
Why Nvidia is making this move
Nvidia is best known for the GPUs that power AI data centers and gaming rigs. RTX Spark marks a significant push into client PC silicon, the chips that sit inside the computers people actually carry around.
The company frames these machines as “personal AI computers.” The bigger idea is a shift toward agent-driven workflows, posing a direct challenge to the traditional app-centric model of computing.
What this means for buyers, rivals, and Nvidia
For buyers, the calculation comes down to privacy and independence versus price. Running a 120-billion-parameter model locally means your data never leaves the machine, which appeals to developers and businesses handling sensitive work.
At $2,599 to start, and potentially $7,000 at the top end, this isn’t an impulse purchase.
The things to watch: how well x86 apps actually perform under emulation, whether developers build software that takes advantage of local AI, and whether the agent-driven model proves useful in daily work.
Disclosure: This article was edited by Diego Almada Lopez. For more information on how we create and review content, see our Editorial Policy.