Nvidia RTX Spark review: Why the local AI platform combining an Arm CPU with a Blackwell GPU is disappointing
After testing three RTX Spark laptops—the Asus ProArt P16, HP OmniBook Ultra 16, and Lenovo Pro 9n—for two weeks, the author concludes that the platform is disappointing in both form factor and readiness. He notes that these laptops are thick and heavy, with noticeable heat and noise; memory expandability and bandwidth fall short of Apple Silicon; shared memory must be configured manually rather than being unified memory; and Windows 11 offers no RTX Spark-exclusive features, making the local AI experience complex and slow. The author believes the problem lies with Nvidia and Microsoft, and that the PC vendors themselves are not at fault.
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AI score 55
The author tested three RTX Spark laptops for two weeks, explaining from both form factor and platform readiness why the local AI experience falls short of expectations.
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I was so excited for Nvidia RTX Spark and its unique combination of Arm CPUs and Blackwell GPUs, but it is crushingly disappointing.
❌ RTX Spark laptops are heavy, hot, loud, and wrong for AI agents
❌ RAM scalability and bandwidth fall short of Apple Silicon
❌ Manually configured shared memory, not unified memory
❌ Windows 11 offers no unique RTX Spark functionality or platform capabilities
❌ Local AI is complex, slow, and unlikely to meet anyone's needs
John F. Kennedy once observed that "Success has many fathers, but failure is an orphan." But with the Nvidia RTX Spark platform, the failures are many and the blame can be assigned to multiple parties. So many things had to fail all at once for this platform to land the way it has.
The only parties involved that are blameless in this fiasco are the PC makers. I've not used all the initial RTX Spark laptops, but I have used three--the ASUS ProArt P16, the HP OmniBook Ultra 16, and the Lenovo Pro 9n--for over two weeks. Each is a premium, handsome, and well-made device that communicates its makers' design expertise. ASUS, HP, and Lenovo, at least, have upheld their ends of the bargain.
The problems with RTX Spark are many, but they can be broadly organized into two top-level issues: Form factor and readiness. And in both cases, the PC makers can only do what they always do and follow the industry titans on which they are reliant. In this case, Microsoft, which supplies the OS their customers demand, and Nvidia, which makes the RTX Spark chipset that both Microsoft and Nvidia tell them their customers will want.
So let's take a look at both.
Form factor
Compared to conventional PC chipsets, which these days consist of a system on a chip (SoC) with microprocessor, graphics, and NPU chips, RTX Spark is unusual, an outlier. I discuss the architecture below, but the simplest way to describe how and why it's different from traditional AMD, Intel, and Qualcomm designs for PCs is that RTX Spark is engineered specifically for local AI.
AMD, Intel, and Qualcomm make families of PC chipsets. AMD and Intel have offerings that specifically target laptops and desktop PCs, and Qualcomm has offerings that specifically target laptops (and, semi-coincidentally, NUC-type mini-form factor PCs that are basically laptops without screens). Nvidia, in contrast, makes a single chipset, the N1X. That there are two nearly identical models--one with an 18-core CPU and a 5120-core CPU and the other with a 20-core CPU and a 6144-core GPU--is mostly a coincidence or byproduct of the chip manufacturing process, not a strategy.
That said, while there are those two N1X models for laptops, there's also an N1X variant--again, with a 20-core CPU and a 6144-core GPU--for desktop PCs that only varies in the amount of heat--as expressed by TDP, or Thermal Power Design--it can expend in normal operation. Where the laptop...