Microsoft Surface Laptop Ultra: NVIDIA RTX Spark means business

NVIDIA officially entered the Windows PC race this week, and its arrival brings a formidable new competitor to the premium AI PC market. With its RTX Spark platform, NVIDIA is bringing its Grace Arm CPU architecture, Blackwell GPU technology and extensive software ecosystem together in a new generation of Windows laptops. Microsoft’s Surface Laptop Ultra is among the first systems to showcase this collaboration, leveraging NVIDIA’s tech and putting it squarely in competition with Intel, AMD, Qualcomm and even Apple for high-performance local AI and creation-optimized laptops.

For Microsoft, the partnership expands the capabilities of Windows on Arm considerably, particularly for local AI development, content creation and other demanding professional workloads. Starting at $2,599.99, Surface Laptop Ultra is clearly a premium offering, but its combination of processing horsepower, large, unified memory capacity, and premium industrial design gives it an interesting position in the market.

My personal testing suggests NVIDIA and Microsoft have delivered a compelling platform with strong AI throughput, graphics performance and competitive CPU compute. Just as importantly, the Surface Laptop Ultra offers a glimpse of how AI development and local AI agent workflows could become more practical on a portable Windows PC.

NVIDIA RTX Spark brings Grace Blackwell to Windows on Arm

At the heart of Surface Laptop Ultra is NVIDIA’s RTX Spark N1X SoC, combining up to 20 Grace Arm CPU cores with a Blackwell GPU featuring up to 6,144 CUDA cores. Configurations support up to 128GB of unified memory, shared between CPU and GPU. The Surface Laptop Ultra model I tested has this full-fat configuration with an eye-watering $5,899.99 price tag (thanks, memory crunch), though there are lower-cost base configs as noted previously, offering an 18-core CPU with a 5,120-core GPU and 24GB of unified memory.

NVIDIA and Microsoft

Regardless, this architecture is particularly powerful for running on-device AI. Rather than being constrained by the dedicated graphics memory found in conventional laptops with discrete GPUs, RTX Spark can make a much larger pool of memory available to GPU-accelerated applications. This allows larger language models, longer context windows and demanding inference workloads to run locally. It’s similar in design to AMD’s Ryzen AI Max series, aka Strix Halo, in that regard, but with a more potent GPU engine on board.

NVIDIA’s CUDA ecosystem is another important advantage. Developers can leverage familiar tools including TensorRT, PyTorch and llama.cpp, with a base software foundation that also extends into NVIDIA-powered workstations and data center infrastructure.

For organizations building AI applications, this offers a solid development path. Models and workflows can be prototyped locally before moving to larger systems, reducing cloud compute and token expense while allowing sensitive data to remain on-device. (See: Around the corner: Agentic AI PCs that cut token costs.)

Microsoft has also optimized Windows 11 for RTX Spark, with improvements to workload scheduling, power management, memory allocation and application compatibility. These platform-level investments were essential to making NVIDIA’s Arm architecture practical for everyday Windows computing, and I was able to put some of them to the test in the few days I’ve had the machine on hand.

Surface Laptop Ultra: Premium design meets practical function

Microsoft has given RTX Spark an appropriately premium home with this machine. The Surface Laptop Ultra features a 15-inch PixelSense Ultra mini-LED touch display with up to 2,000 nits of claimed peak HDR brightness, a 120Hz refresh rate and excellent potential for creative work requiring high accuracy and wide gamut coverage.

Dave Altavilla

The machine’s aluminum chassis is less than 18 mm thick, and it weighs in at under 4.5 pounds. It’s not an ultraportable per se, but considering the horsepower on board, Microsoft has struck a reasonable balance between portability and performance.

The design is refreshingly understated, with clean lines and rigid aluminum construction. My initial hands-on impressions have been particularly positive, thanks to the keyboard’s tactile response, smooth and responsive haptic touchpad, and bright, high-contrast display.

The larger touchpad should be especially welcome for users navigating complex applications, while the touchscreen adds flexibility for reviewing documents, annotating designs, and interacting directly with creative content.

Connectivity options are also very good, relative to other premium laptops. Microsoft includes three USB-C ports, HDMI, USB-A, an SD card reader and a headphone jack. One USB-C connection features Microsoft’s new magnetic charging mechanism, combining the convenience and safety of a breakaway power connector with the versatility of a standard USB-C port.

Microsoft has also designed the cooling system with large fans and significant thermal capacity, while making the machine’s internal SSD removable and offering good internal serviceability in general. These are practical considerations for professional users and IT departments concerned with reliability, maintenance and long-term ownership.

Battery life and sustained performance under prolonged workloads are important aspects Microsoft focused on for the overall experience, particularly for a machine designed to deliver workstation-class capabilities away from a desk. More on this shortly.

Local AI agents: Moving from inference to action

RTX Spark also supports locally running autonomous AI agents, including one that I tested out called Hermes, which can execute multi-step workflows, access files and interact with applications. Its potential impact spans software development, research, document analysis, business automation and many other disciplines. Hermes provides the agent framework, while supported models leverage RTX Spark’s CUDA-accelerated inference and unified memory.

For businesses, local agents can keep sensitive data on-device and reduce cloud inference costs, provided they’re configured appropriately. However, granting agents access to files, code execution and corporate systems introduces security risks. Microsoft’s Execution Containers and NVIDIA’s OpenShell aim to provide isolation and access controls, though their effectiveness depends on proper enterprise policy implementation.

Hermes running Qwen3.8-27B locally on Surface Laptop Ultra, generating a benchmark report.
Dave Altavilla

To test this capability, I ran Hermes with the Qwen3.8-27B language model locally on the Surface Laptop Ultra. I asked it to extract benchmark charts from an Excel spreadsheet and create a formatted Word report with performance commentary. Hermes autonomously generated and executed Python scripts, processed the spreadsheet and assembled the document in approximately five minutes. Color me impressed.

That’s a respectable turnaround for a task requiring several manual steps. My results demonstrate how local AI agents can streamline reporting and analysis without cloud-hosted model inference. Human review remains essential, but this was a promising demonstration of practical, real-world agentic AI on a Windows laptop.

AI performance: Strong results as expected

My team’s preliminary AI benchmarks highlight the advantages of NVIDIA’s RTX Spark architecture. However, we’re still digging deeper into AI-enabled use cases and performance.

In UL Procyon’s AI Text Generation benchmark using Phi 3.5, a family of lightweight, open-source small language models (SLMs) released by Microsoft, the Surface Laptop Ultra scored 2,703, compared with 2,027 for Lenovo’s Intel Core Ultra X9 388H-powered IdeaPad Pro 5, an advantage of approximately 33%.

Dave Altavilla

The difference was even more substantial in MLPerf’s Flux 2 Klein 4B image generation workload, where the Surface Laptop Ultra delivered 26.97 images per minute versus 9.96 for the Lenovo machine, or roughly 2.7 times the throughput.

These results demonstrate the platform’s potential for accelerating local inference, image generation, agentic workflows and other AI workloads. Actual application performance will depend on model selection, software optimization and available system memory, though NVIDIA does provide a nice memory partitioning tool in the NVIDIA App for Windows.

Content creation, gaming and battery life: Blackwell’s versatility

RTX Spark’s Blackwell GPU delivers impressive graphics performance, extending the Surface Laptop Ultra’s capabilities beyond AI development and everyday creation or productivity tasks.

Dave Altavilla

In 3DMark Steel Nomad Lite, the Surface Laptop Ultra achieved 98.29 FPS, more than double the 46.07 FPS of Lenovo’s Core Ultra X9-powered IdeaPad Pro 5. In the ray-tracing-focused 3DMark Speed Way test, it delivered 30.31 FPS versus 19.72 FPS for the ASUS ROG Flow Z13, powered by AMD’s Ryzen AI Max+ 395 and Radeon 8060S graphics.

Dave Altavilla

Actual gaming performance was similarly strong. In Cyberpunk 2077, the Surface Laptop Ultra averaged 71.05 FPS, ahead of the ROG Flow Z13’s 63.76 FPS. However, the AMD system narrowly led in The Talos Principle 2, delivering 89.5 FPS versus the Surface’s 84.5 FPS at 1080p medium settings.

CPU performance for tasks like 3D rendering also holds up well. In Cinebench 2026, the Surface scored 6,787 in the multi-threaded test, edging out the AMD-powered ROG Flow Z13’s 6,546. Notably, the Surface retained 99% of its multi-threaded performance on battery power as well.

For creative professionals, native Arm applications including Blender, DaVinci Resolve and Adobe Photoshop offer opportunities to leverage RTX Spark’s potent GPU. However, Windows on Arm compatibility remains a consideration. Microsoft’s Prism translation supports many x86 applications, but specialized software, drivers and certain games (like EA anti-cheat-supported titles currently) may still encounter limitations.

Dave Altavilla

Battery endurance was respectable for the Surface Laptop Ultra, at 14 hours and 35 minutes in my PCMark video playback testing, though competing mainstream thin-and-light laptops lasted considerably longer. The Surface Laptop Ultra and RTX Spark operate within a different power envelope, however, more akin to a beefier gaming laptop, rather than a svelte 2 – 3-lb business machine.

Final thoughts: A serious new AI Windows PC competitor

The Surface Laptop Ultra marks an important milestone for NVIDIA’s expansion into Windows PCs and Microsoft’s ambitions for high-performance Arm-based computing.

My initial testing shows the RTX Spark-powered Surface Laptop Ultra delivers exceptionally strong AI acceleration, competitive multi-threaded CPU performance and impressive graphics horsepower. Combined with Microsoft’s premium industrial design, extensive connectivity and I/O options, and Windows platform integration, RTX Spark makes a convincing first impression.

Starting at $2,600, this is a specialized, premium system, and mainstream business users will find more economical alternatives to be sure. However, for developers (even vibe coders), creative professionals and organizations evaluating local AI workflows, the Surface Laptop Ultra offers a compelling combination of performance, beautiful industrial design, portability and local AI capability, especially with its higher-tier memory configurations.

NVIDIA has arrived in the Windows PC market with serious technology, and Microsoft’s Surface Laptop Ultra is an impressive first showcase of what this new partnership can deliver.ComputerworldRead More