In a weird way, I’ve been thinking about the idea of a Googlebook for well over a decade now — despite the fact that such a product has only officially existed for a matter of months.

I’m relatively unusual in the world of tech journalism, y’see, in that I’ve been both writing about Android and ChromeOS since the platforms’ earliest days and actively using devices from both ends of those ecosystems in my own day-to-day life that entire time. Most tech writers tend to be iPhone owners and Chromebook skeptics who see this part of the digital world from an outside view — once a year or so, when significant new devices come along for assessment — without having the perspective of someone who’s truly immersed in it day in and day out.

That distinction is always painfully apparent when you read a review that waxes on endlessly with out-of-touch iPhone comparisons and comments about the limiting nature of Google’s ChromeOS concept — positions that simply aren’t accurate for those of us who live in these ecosystems and embrace the philosophies they offer.

This won’t be one of those reviews, and I perhaps more than anyone have been champing at the bit to get my hands on one of Google’s new Android-ChromeOS-combining Googlebooks since the vaguest concept of these devices first appeared on the horizon earlier this year.

So keep that in mind when I tell you, coming from the perspective of someone who very much wanted to love this: Using a Googlebook is an extraordinarily strange experience — especially when you’re treating it like a regular laptop, as it’s being positioned by Google, and relying on it to get real work done.

But amidst all the oddness, there are some true high points along with plenty of intriguing, if unfinished-feeling, potential.

Here’s what it’s been like trying to actually work on a Googlebook — specifically, the Lenovo Googlebook, which sells for $1,149 (and was provided to me as a short-term loaner from Lenovo for the purposes of this article).

The Googlebook groundwork

First things first, let’s back up a minute and set the stage for what we’re even talking about here.

The Googlebook is a new type of laptop created by Google and built by a variety of third-party device-making partners — Acer, Asus, Dell, HP, and Lenovo, to start.

It’s meant to represent an evolution of sorts from the Chromebook, the initially simple laptop Google launched in 2012 and slowly morphed from a barebones web portal into an “everything OS” — a system that runs web apps, Android apps, Linux apps, and even sometimes Windows apps, for businesses that have specific needs that can’t be addressed in any other way.

But while ChromeOS and Android grew closer and more connected over time, Googlebook OS — the awkwardly clunky name of the operating system at the heart of every Googlebook — sets all of that aside to aim for a fresh start. The software here sports Android at its core alongside a variety of optimizations designed to bring in bits of ChromeOS-like elements and make everything seem more suited to a laptop setting.

With that in mind, starting to use a Googlebook is both immediately familiar and vexingly confusing. The interface feels a lot like Android, which is nice, but it also doesn’t quite feel in line with how you expect to work on a desktop computer. It’s a jarring sort of mashup, and it’s tough to wrap your head around to get comfortable working.

That’s true for relatively small touches like having the clock in the upper-left corner of the screen instead of in the lower-right corner, where’d you expect it on most non-Apple-made computers. It’s a little thing, but it keeps throwing me whenever I try to glance at the time during the day. That approach is similar to Android, yes, but it just doesn’t feel right in this environment or with what pretty much all of us who’d be considering this kind of device have been trained for ages to expect with a desktop computer experience.

It’s true, too, for keyboard shortcuts, which don’t work the same as they did on ChromeOS — even just basic, common things like opening items on the taskbar. (Googlebook OS does have an impressive array of customizable keyboard shortcuts, if you find ’em, but there’s a ton of new combinations and muscle memory to be learned.)

The confusion is probably most prominent, though, on the app front, where Google is really leaning hard into the Play Store and the idea of Android apps being the primary way to get stuff done, despite the fact that Android apps often aren’t ideal — or even available, in some instances — in a productivity-oriented, desktop computing scenario.

At least one of Google’s own apps addresses this elegantly. Installing Google Calendar from the Play Store basically just gives you an app-like shell around the Calendar website, and you can use the Android app’s widget alongside that, if you want. (The downside is that you can’t use the equivalent Android app in full even if you want to, as there’s no straightforward path to install it — and, strangely, the same web-widget combo is not available with other Google apps, like Gmail or Drive, which give you only the web version and no option to use any associated Android widgets.)

And since the version of Chrome on a Googlebook looks and feels like the full desktop version of the browser — like what you’d expect on a Chromebook or any other desktop computer — relying on this unusual mix of web and Android interfaces for productivity is mostly OK. Mostly.

Working in Docs, with as few as five or six tabs open, I continue encountering an occasional issue where the tab just blanks out for a second or two and then comes back — which, suffice it to say, isn’t exactly optimal for working.

The email app I use, Superhuman, appears to be completely incompatible here. The web version (which is powered by a Chrome extension) errors out anytime I open it, and the Android app is clearly not meant for large-screen, keyboard-and-mouse use and presents an incredibly awkward experience as a result.

The productivity tool Notion, meanwhile, came up for me as one of the Googlebook’s suggested tools that’s optimized for desktop use, so I followed that direction and installed the Notion Android app — only to find that the app is much more awkward and limited on a laptop than the regular Notion web experience, where all the functions are available and the keyboard shortcuts work as expected. So I decided to try to install the Notion web app for easy ongoing access to that, and I encountered a mysterious error.

D’oh.

Then there’s something like Slack, which you can install from the Play Store but with an accurate warning that it’s “better on the website.” So, OK: You go to the website, try to sign in and install the web app version of it from there, and…there’s that blasted “cannot be installed” error again. (Google says it rolled out an update last week that allows any web page to be installed as a web app, but as of this writing — even with that update present on my device — the same error-encountering pattern persists.)

Other apps appear to work fine but then behave in odd and unexpected ways. I tried to install the Android version of Vivaldi, for instance, and it installs and opens without issue — but then returns an error anytime I try to actually open a website within it. That definitely doesn’t happen on a Chromebook, nor do the other aforementioned issues.

There’s just a lot of weird stuff like that, where it feels like a typical Google not-quite-fully-baked product. To be fair, that may be at least in part because of third-party app developers not yet supporting what needs to be supported for full optimization in this new environment — but either way, that’s the experience you get on a Googlebook right now, and it’s an all-too-familiar chicken-and-egg challenge that there’s no telling how long might take to see resolved.

On a somewhat related note: While the ability to install Linux apps is technically present on a Googlebook, it isn’t at all a user-friendly experience. Linux app installation is available only in a limited manner within the confines of a command-line terminal, and any such programs consequently don’t integrate into the launcher or the main Googlebook interface. That means there’s no real way to use them as a part of the standard Googlebook experience — which is a shame, as having those more traditional desktop apps available on ChromeOS went a long way in filling in pertinent function gaps for a lot of people and businesses. (Google says better Linux app support is vaguely “on the roadmap.”)

The various layers Google created to make Windows apps available for businesses in ChromeOS aren’t present in this environment, either. The official line, as relayed to me by a Google spokesperson, is that “Googlebook takes a fundamentally different architectural path than previous platforms” and they “aren’t attempting to patch together legacy PC software layers or rely on Windows emulation to make a laptop functional”:

Instead, Googlebook OS is built directly on the Android tech stack with the desktop foundations of ChromeOS, pairing the world’s largest native app ecosystem with an uncompromised, full desktop Chrome browser.

This makes it easier than ever for developers to build a true desktop-class app experience.

That’s all noble enough in theory — but as a prospective Googlebook owner right now, what good does any of that do when most developers haven’t yet built those “true desktop-class app experiences” for this environment? Or when you’re a business user whose company has the very same sort of “legacy” software requirements that led Google to work so hard on Windows app support for Chromebooks and maintain that option in that arena?

Pros, cons, and more Googlebook confusion

Let’s break from the strange stuff for a minute to focus on some positives — because, again, there is something undeniably cool about experiencing Android in a laptop form and seeing all the ways a Googlebook works hand in hand with an Android phone to make life easier.

First and foremost, Googlebooks stray from the longstanding minimalist Chromebook standard to give you a fully customizable desktop — with the ability to create any arrangement of shortcuts and widgets, just like you can on an Android home screen. That is absolutely a welcome progression from the more limiting ChromeOS approach and something I’d long hoped to see in that domain, and having those familiar forms of interactive info right in front of you while working is an incredibly helpful addition.

Being able to easily access the files on your phone without any extra hoop-jumping is also a nifty touch, for the moments when such a need arises. Once your Googlebook is paired with your Android phone, you simply open the Files app on the laptop, and you can see and interact with any files on your phone right then and there. (That said, the Files app is otherwise much more barebones and limited than its ChromeOS equivalent, unfortunately — so you can’t, for instance, drag and drop directly from the phone to any specific folder on your local or Google Drive storage.)

As far as hardware is concerned, Lenovo did a bang-up job with its inaugural Googlebook device. This is one seriously nice laptop — a pleasure to hold, with an almost silky-feeling smooth texture on the top and a thoughtfully ridged bottom for extra grippiness when you carry it. The system has a beautiful (and big!) 15.3″ display, an excellent keyboard and trackpad, and surprisingly great speakers. Those boxes are all checked off.

But it’s the experience inside the hardware that means the most, here in particular — so, back to that:

Native app installation aside, one key selling point of the Googlebook is how it’s able to stream apps from a connected Android phone — letting you run an app from your phone on the computer, in other words, without having the app installed locally on the Googlebook itself.

It’s a slightly confusing concept to wrap your head around, especially since you can also install most of the same apps from your phone directly onto the Googlebook if you want (and, given that this is a native Android device, installing and running Android apps on it is absolutely smoother and snappier than what you typically experience on a Chromebook). Because of that — just like with the equivalent streaming option that had been available on ChromeOS in recent years — it seems like something that’s bound to be more befuddling than beneficial for most people, most of the time.

That being said, I have had a couple of situations come up where it seemed like the feature might be handy. First, I needed to get a two-factor authentication code out of Authy, which is available only as a mobile app. A perfect use-case, right?

Well, not exactly: The Googlebook wouldn’t let me stream the Authy app from my phone and instead gave me an error: “Can’t cast content. This content is restricted.” So then I thought maybe I’d just install Authy directly onto the Googlebook instead, but alas: The app “isn’t available on Google Play on this device.” Bah.

Another time, I tried to open Google Wallet from my phone to get some info off my insurance card, which I have stored in that service. That worked, at first — but then the app kept hanging on a loading screen anytime I tried to open anything.

The one scenario where the app streaming has been helpful is with notifications: Anytime you get a new notification on your connected Android phone, it shows up as a pop-up in the upper-right corner of the Googlebook display. The same actions that’d be present on the notification on your phone, such as marking something as read or replying in-line, are also present on the computer, and you can click on the notification to open the associated app in full on your laptop — just like you would on your phone, only everything happens within a window on the Googlebook.

That’s a clever little sleeper feature and arguably the best part of the app streaming capability, even if you don’t necessarily think about the fact that you’re using app streaming when it happens.

Another key selling point is the addition of AI-oriented features into the Googlebook operating system. This includes a Magic Pointer feature that lets you wiggle your cursor to summon Gemini and ask it about any specific area of text or visual on your screen — which is fine but not something I find myself actually using often. Its most useful-seeming promise is being able to act on information, like creating a calendar event based on a specific area of an email or text message on your screen, but its accuracy in getting the details right in such scenarios has been pretty hit and miss in my experience.

Then there’s the integrated Rambler system for conversational voice-to-text conversion (as seen on Google’s recent Pixel phones). It works well, but by design it isn’t a direct dictation tool; instead, it adjusts and rewrites your rambling speech (hence the name) to make it better, in its view. That makes a lot of sense when you’re spouting off a quick text message while walking or driving, but unless you don’t mind losing your own specific style, intentions, and voice with longer computer-crafted communications, it doesn’t seem like something you’d be using much in a business capacity — though it can certainly be handy to have available on occasion.

As is often the case with Google products and AI features in particular, some of the smaller, less headline-making touches on the Googlebook are much more interesting than the flashy marquee features.

All in all, it’s a perplexing picture.

The Googlebook productivity puzzle

More than anything, the question that keeps coming to my mind — again, as someone who fully embraces Android and frequently works on a Chromebook — is simply: Who is this meant to serve? And, in its current state, for whom will it be a meaningful upgrade and enticement over other existing options?

I keep thinking how this exact setup would make for an absolutely brilliant souped-up Android tablet interface, with the right kind of hardware around it. You’d have the familiar Android-like environment, optimized for a larger screen, and the ability to pair that with a more desktop-like experience in the core Google apps — including Chrome, for a less limiting active web experience when you connect a keyboard (or flip around a convertible device to have one present).

As the Googlebook stands now, though, I just don’t know that it’s a great replacement yet for a Chromebook — or any other laptop — particularly when it comes to getting actual work done. At best, it feels like a fairly linear progression with some awkward adjustments and asterisks. At worst, it’s gonna be a real challenge for some people to use in the way they need a laptop to work. And I’m just not sure what’s being added, from a practical perspective, that makes it all worthwhile.

What we can say is that Google has a history of launching products that are still rough around with the edges, and sometimes, those products evolve over time — sometimes quite quickly! — and end up becoming incredible. Heck, think how much ChromeOS changed from its earliest form to the way it is today.

At the same time, Google also has a pesky habit of pivoting, giving up, and failing to follow through on once-heavily-hyped products. A fair amount of the Googlebook’s early shortcomings come down to convincing third-party developers to buy into the platform and invest the resources in making their apps work well on it, too — which is the exact same chicken-and-egg challenge that’s kept promising Google concepts from blossoming before.

For now, the Googlebook is an awkward start with plenty of potential. Where it goes next is anyone’s guess — and something that, to some degree, may depend on how many people are willing to take the leap with it early and wait for it to evolve.

It’s all relative, but if you want to scope out the likely shape of the tech device industry in five years’ time, you have to think of the likely shape of the replacement cycle, and right now it seems to be shifting toward Apple. 

That’s going to become more important to tech purchasing as the years roll by and is also likely why you’ll see other manufacturers become even more competitive as they try to stop the tide. It is open to question if they will be able to do so, given that even five years ago Apple still seemed far less dominant, which is no longer the case.

Shrink when you’re winning

If you look at the devices that are being sold, you’ll see one key thing: In the face of memory and component cost-driven price hikes, sales of PCs and smartphones are falling fast. Apple isn’t immune to this macroeconomic trend, so it is also seeing decline, but the relative rate of this decline is less steep, meaning the company is growing its market share even as the industry shrinks.

Gartner says the Mac share of the PC market rose to 10.5% in Q3, up from 8.8% a year earlier, even as Mac sales fell 7.1%. The figures vary by analyst (IDC has Mac share at 9.5%, Omdia at 11.7%), but all three show a gain. 

In smartphones we’re seeing something similar, with Counterpoint Research giving Apple a new record 22% of global smartphone sales in Q3. While it’s true that Apple is achieving lower unit sales in both categories, its decline is far beneath the industry average.

When everyone’s prices rise

Apple has had to raise prices across all its devices but has been able to lean into the sheer scale of its market to help dilute the impact. Lacking Apple’s scale, smaller vendors have been unable to follow suit. This has led to PC and smartphone manufacturers raising prices on their devices to such an extent that Apple now seems to be a good value option. 

Counterpoint Research Director Tarun Pathak caught the mood: “Apple is still gaining new users across categories, and it will become increasingly difficult for competitors to make an Apple user switch to their operating system,” he said.

Shoppers who can still afford to buy can’t help but see that while Apple’s products cost more, everybody else has raised prices to similar levels. It means Apple is being judged differently. When everything costs roughly the same, the value it offers looks different. 

That thousand-dollar smartphone you always wanted but couldn’t justify purchasing seems more viable now that the brand you opted for instead just raised prices to the same level.

Today’s buyers, tomorrow’s upgraders

Now think about what this means 3-5 years from now. It means a growing chunk of PC or smartphone owners will be looking to upgrade their Mac or iPhone. 

So far at least, people tend to stick with Apple once they arrive there. Consumer Intelligence Research Partners puts iPhone loyalty at 87% among recent purchasers, a three-year high, which suggests that this year’s buyers are likely to stick with it once they need to upgrade. Satisfaction points the same way: Apple ties Samsung for the top spot in the American Customer Satisfaction Index’s 2026 personal computer satisfaction ranking, with a score of 81, even as industry-wide satisfaction fell 4%. 

The longer the PC and smartphone market decline continues, the greater the impact of this trend will become. If Apple manages to keep declining at a slower rate in comparison to other ecosystems, its relative market share will continue to grow. 

That share is likely to sustain itself into subsequent purchasing cycles. Apple also benefits from the first generation of M1 Mac owners, who are only now reaching the point when an upgrade seems necessary. (Don’t forget that between 2020 and 2022, the success of Apple silicon drove Apple’s PC market share from 6.6% in 2020 to 10.8% in 2022, setting a new trend line.)

Why IT should pay attention

That’s more than a curious observation for Apple fans. It’s also something that should matter more to enterprise tech, as it suggests that the need for investment in device management and Apple hardware is going to accelerate through the downturn. It hints that support for these platforms will become a business necessity; that if your teams continue refusing to support Apple platforms and aren’t prepared to change that, then you may soon be searching for different IT teams.

Now please subscribe to my daily, human-curated Apple-related news headline feed at The Core, or follow me on BlueSky, LinkedIn, or Mastodon.

Welcome to the week Apple showed us how serious it really is about artificial intelligence on Macs, with the company making more moves to deliver the tech in the most cost effective, responsible way. While it’s true that today is iPhone Duo pre-order day, that’s arguably not the big news. 

It is not the big news because Apple this week made huge steps in AI. Not only have its researchers come up with a nifty tool to turn Macs into distributed inferencing data centers, not only does the company now have a plan for Apple Intelligence in China, but it has also worked with Meta to make it possible to run on-premises instances of Muse Spark Open on a couple of Mac Studios. Its machine learning team also introduced a new version of MLX that enables AI researchers and developers to run large language models (LLMs) locally on Mac Studio with Apple silicon. 

What’s new to MLX from Apple?

In case you’d missed it, MLX leverages the unified memory architecture of Apple silicon, which is invaluable if you want to build new inference and fine-tuning methods. Over the past year, the ML team has worked on “several key innovations” to make it easier and more efficient to “run state-of-the-art LLMs locally on recent Apple silicon.”

These improvements include:

• Software support for the Neural Accelerators in the GPU of the M5 family of chips
• Low-latency communication across several Macs using Remote Direct Memory Access (RDMA) over Thunderbolt
• Efficient implementations of recent popular architectures such as mixture of experts (MoE)

The release leans heavily into what Apple’s teams have been doing with Muse, and once again demonstrates how the very architecture of Apple silicon supports AI inferencing. That’s no surprise to anybody at this point: not only have I been banging on that drum regularly, but almost anyone who is anyone in AI development and research already works on a Mac.

LLM inference with MLX on Mac Studio

A new white paper from Apple’s machine learning team shares what it has been doing with MLX, along with significant statistics concerning how well its systems support Muse Spark Open, Meta’s new open-weight frontier model. 

“On a cluster of four Mac Studios, Muse Spark Open generates over 36 tokens per second, well above average human reading speed,” they said. 

That’s impressive. It means for the cost of four Mac Studios, a business can run a full-strength, frontier-class model with almost a trillion parameters, on-premises, securing company data while extracting whatever benefits there are to be extracted from the use of it.

Mac Meta matters

Apple and Meta collaborated on making it possible to run Muse Spark Open AI models on Macs. It’s a shrewd move for both companies, given the growing desire to run powerful AI models locally rather than in the cloud. As a result of this work, it’s possible to use Muse Spark Open on two or four Mac Studios to engage in all kinds of agentic tasks. 

Commenting on this on X, new Apple CEO John Ternus wrote: “Amazing to run a model of Muse Spark Open’s caliber and scale this efficiently, right from your desk. Mac Studio keeps pushing the boundaries of on-device AI!” 

Meta’s AI chief Alexandr Wang pointed out that this is in part made possible by Apple’s Unified Memory architecture, which can provide sufficient memory to run these models.

Your Macs. Your supercomputer

“Apple’s unified memory architecture lets the M5 Ultra’s integrated GPU use up to 512 GB per Mac Studio, so two machines can hold an entire model,” Meta explained. “And the chip’s 1.2 TB/s of memory bandwidth is fast enough to read the small slice each token needs. The result is two Mac Studios behave like one supercomputer with a terabyte of unified memory.”

Meta says it tested the system using agentic workflows running entirely on-device, including applying bug fixes and new features to an open-source Mastodon client and driving DaVinci Resolve to review footage and transact tasks. The use of DaVinci Resolve makes this commentator curious, given that Apple is expected to introduce new pro Macs this month. The idea that you may be able to run tasks like this on other Macs will surely be something Apple’s developers are thinking about.

One more thing

Step by step, Apple is defining the playground for AI. In doing so it is attempting, as Greg Joswiak, Apple’s senior VP of worldwide marketing, told TIME, not to make AI for “the lunatic fringe,” but to create an ecosystem for artificial intelligence that will actually help people — a strategic approach that, if it comes together, will help maintain Apple’s position at the intersection of computing and the liberal arts.

(Read my Mac Studio review here.)

Now please subscribe to my daily, human-curated Apple-related news headline feed at The Core, or follow me on BlueSky, LinkedIn, or Mastodon.

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.

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.

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.

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%.

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.

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.

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.

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.