Right now, you are probably paying a monthly subscription to rent a sliver of a server farm in middle America. You ask a cloud chatbot to write an email, it pings a data center and you get an answer.

It’s fast, magical and a massive trap.

We are handing our personal data, our workflows and our wallets over to massive tech conglomerates, and for what? To prop up a cloud AI bubble that looks ripe for bursting, encourage more aggressive build-outs of data centers nobody wants, and feed an ever-learning black box with more and more of our sensitive information.

But there’s a different way. It’s a way I’ve always believed in. The future of AI is local.

After spending the past two weeks stress-testing the new Nvidia RTX Spark laptops — and with Apple’s M6 MacBook Pro rumored to arrive next week with vast AI acceleration — the hardware has finally crossed the threshold.

You no longer need the cloud. It’s time to build your own personal, local moat. But to do so the right way is different to what you’re used to. And I’m going to start from the beginning and break some things down for you.

What is an AI agent?

A standard chatbot waits for you to ask a question. An agentic AI has autonomy.

You give it a goal, a set of tools (like access to your file system or a web browser) and permission to execute tasks on its own using a ReAct (Reason + Act) loop. It thinks, acts, checks its work, and continues until the job is done.

Now, this is all fair and good, and you see cloud options available like Meta Muse. But I’ll be real, the difference in control and privacy between a zippy cloud agent and a local agent makes the time you’ll wait for your on-device one to get things done well worth the wait.

P.S. you can make time for other fun things while it works away, but I’ll get to that.

How to set it up (the Hermes Agent method)

Now I know there’s going to be several enthusiasts out there who may have a debate about which is best between the likes of Hermes Agent, OpenClaw or LM Studio Bionic. Ultimately, this is personal taste and (in my opinion) the easiest to transition to from using a cloud AI like my Gemini Pro subscription.

Your choice here will depend entirely on your laptop’s memory:

• 8-16GB RAM: Stick to smaller 7-8B parameter models like Llama 3.1 8B (as of the time of writing this). They are lightweight and fast for quick tasks, but prone to getting confused if you throw anything complex at it.
• 32-64GB RAM: The sweet spot. You can run 30B-70B parameter models like the Qwen 3.8 27B option I’ve been running on this Asus ProArt P14 I’m testing.
• 128GB+ RAM: The monster tier. Chances are you already know full well what you aim to do with AI with this much memory. But to catch everyone else up, you can run massive, enterprise-grade models like Qwen 3.8 Flash-Next — that can rival GPT-4, completely offline.

Now this is the world of open source, so there’s so many to choose from. A great source of reference is going to be modelfit.io. I used it when I got properly started!

How to shrink a brain (quantization)

Now, there is an extra wrinkle to this that you need to pay attention to. There are some models that sound like massive, multi-billion parameter options that usually require a refrigerator-sized server rack. How does it fit on your laptop?

The secret is a process called quantization.

Think of quantization like shrinking down a massive, uncompressed RAW photograph into a JPEG. The AI engineers take the incredibly precise, memory-hogging mathematical weights of a model and round them down. You lose a microscopic fraction of absolute precision, but the file size shrinks drastically.

For the ProArt P14, I am downloading a model called Qwen3.8-27b-gguf Q3_K_XL. To translate that alphabet soup: it’s a brilliant 27-billion parameter model that has been quantized (that’s the Q3 part) so perfectly that it fits entirely within the 32GB of RAM.

Pro tip: When you go to download your models, look for those “GGUF” and “Q” tags — they are the cheat codes that let massive AI brains run on consumer hardware.

Cloud vs. Local: the coffee break rule

There are two big differences I found between using cloud and local AI. The first is speed.

Cloud AI is instantaneous — throwing vast data center computing power at your prompt to give you a millisecond response. Local AI runs on your laptop’s silicon, so naturally it’s slower.

If I ask my local agent to parse a 50-page PDF and cross-reference it with my calendar, it might take three to four minutes, whereas on cloud that’d happen in 30-60 seconds.

It’s slower for sure, but a trade-off I’d absolutely make for the reasons I spoke about up top: privacy, and the ability to build my own personal brain without spending a penny for the tokens I burn.

And when it gets more complex — like me tasking my team of agents to go through my emails and calendar, take note of the previous meetings I had, understand the context of the wider world of tech news, track any analytical trends in the site’s traffic and craft my day of work, it can take a little bit of time.

The trick is to treat it like a real assistant: give it the task that would’ve normally taken you a while to do yourself, and spend that time doing something else. For me, it’s that calm breakfast in the morning or a walk around the park. And by the time you sit back down at your desk, the work is done.

The 4 rules of “parenting” a local AI

Beyond that speed difference, you have to completely rewire how you talk to your computer. Cloud AIs are designed to be frictionless, constantly updated by engineers behind the scenes. Local AI is like a raw blank slate. It’s only as useful as what you give it, so follow these four rules:

You are the sole provider of its data diet

Cloud AI is constantly scraping the internet and updating its worldview. Your local AI is completely isolated. It only knows what you feed it.

If you want it to understand how you format invoices, or the specific tone you use in emails, you have to explicitly provide those documents. It isn’t going to magically know you from the get-go.

Make your prompts hyper-specific

Since cloud AIs have billions (maybe trillions) of data points of context, they can read between the lines of those vague, half-baked questions you have.

Local AI is intensely literal. If you give it sparse instructions, it will give you a sparse, unhelpful output. Instead of “organize my downloads,” think “organize my downloads by file type and rename them to be more contextual with what they are.”

The carrot, not the stick (reinforcement)

To highlight, I don’t mean the “reinforcement learning” AI engineers are doing across the globe on frontier AI, I mean like I learned from teaching my nephew new skills. Something more human. You have to tell local AI to remember the victory.

If it nails that spreadsheet format exactly as you wanted it, reply with: “This is perfect. Save the way you did this into your memory.” Give it a treat so it repeats the behavior.

BTW, you don't need to give the agents names like I did. It just helps me organize them.

Build its mind map in Obsidian

An AI without a long-term memory is just a calculator. To make it genuinely useful, give it a digital filing cabinet. I use Obsidian, a free markdown note-taking app that saves files locally to your storage.

Just point your Hermes agent at Obsidian with a prompt like “can you take everything you’ve learned about me over our past interactions and put it into an Obsidian vault?” And from there, you’ll see the synapses start to form and connect.

The economics of owning your own brain

Now, before I sign off on part one, let’s address the elephant in the room: hardware is expensive. It’s actually one of the reasons I believe the future of AI is local, because these damn cloud AI infrastructures have jacked up the price of memory!

But you have to look at the math of the cloud tax. Right now, you’re probably paying $20 a month for a mid-premium tier service, and if you try to do anything more adventurous, you’re met with limitations.

That’s hundreds of dollars a year in digital rent just to borrow someone else’s server. When you run local AI, the ongoing cost is zero. That means no limitations on what you can do, no restrictions on the amount of images and videos you can generate in Comfy UI. You buy the hardware once, and the open-source software is free.

It’s the difference between renting a cramped apartment where your landlord reads your mail, versus owning your own house. Over a two-to-three-year laptop upgrade cycle, this machine pays for itself in canceled subscriptions — provided you know how to use it.

Outlook

And that’s what I’m here to do. Over the next few weeks, I’ll give you a look into my local AI workspace, introduce you to my first agent “Jeeves” and the rest of my team, and show you how to extract the most value out of it really easily.

It’s going to be a journey, and I can’t wait to see what you come up with. But any questions whatsoever, throw them in the comments.

More from Tom's Guide

• Would you give up ChatGPT to stop AI data centers? Reddit's answer was brutal
• Chatbots and agents like Muse are getting a face — but does that make us trust them more? Here's what this AI expert had to say
• Joseph Gordon-Levitt warns the real AI threat isn’t killer robots — it’s the companies building them

Nvidia and Microsoft just introduced a new laptop category: the RTX Spark platform. While the best laptops are designed for productivity or gaming, these new notebooks give creators and AI coders powerful machines that let them work on the go.

The promise of offline AI work will certainly appeal to some customers, but it also makes RTX Spark laptops a relatively niche offering. That was my main takeaway from testing the HP OmniBook Ultra 16. While impressive, it’s too overpowered for everyday work and relatively underpowered for gaming. Due to that, RTX Spark laptops might struggle to compete with their more popular direct competitor, high-end MacBook Pros.

To better understand who these machines are actually for, I reached out to Tom Mainelli, Group Vice President of Device & Consumer Research at IDC, for his take on where RTX Spark fits right now and where it might go from here.

Early adopters, developers, and creators

RTX Spark laptops target a narrow group: AI developers, content creators, and early adopters. These are premium notebooks built for people who already understand what the platform offers and why the price is what it is.

“These are outside the budget and needs of mainstream users, for now,” Mainelli said. At the same time, he sees them as a preview of where the PC industry is headed. The various configurations support different workloads, but the overall pitch is the same: a high-end Windows machine that can handle local AI work in a way previous laptops couldn’t.

Competing with MacBook Pro and gaming laptops

Mainelli positions RTX Spark notebooks as competitors to similarly configured MacBook Pros. Both platforms use unified memory, which makes them better suited to running larger models locally than traditional Windows laptops with discrete GPUs.

The difference is that this is an Nvidia system-on-chip, so it brings native CUDA support to Windows on Arm — something Windows laptops haven’t had before. Windows has also added new setup features that make it easier to install and run local agent platforms such as OpenClaw, Hermes, and Perplexity Computer in a more secure, managed way.

Though Nvidia didn't market them directly as gaming laptops, it did show games running on RTX Spark systems. And given Nvidia’s gaming origins, it’s natural to wonder how these machines function as gaming systems. “Few vendors are marketing their RTX Spark systems as gaming systems, which typically have high-end discrete GPUs, but they appear to offer a solid gameplay experience,” Mainelli said.

My team and I noted that sentiment in our reviews of RTX Spark laptops, which tend to offer performance on par with RTX 5070 gaming laptops. Still, these aren’t — and shouldn’t be considered — gaming laptops. Gaming is simply an option, not a primary function.

Unified memory architecture

The unified memory design could change the value proposition. On the high-end 128GB configurations, you can allocate up to 96GB to the GPU. That’s far more than you can get with a discrete GPU in a laptop, and it means you can load sizable models into memory and potentially run more AI inference workloads locally.

“Because the unified memory architecture makes it possible to allocate more memory to the GPU than you can buy in a system with a discrete GPU, it could change the value proposition,” Mainelli said.

In theory, that could reduce what AI developers spend on cloud-based tokens. In practice, Mainelli said it’s still early. It requires a savvy user who’s willing to spend up front on the hardware and then experiment with local models to get the best results.

Cost is the biggest barrier

When I asked about the practical limitations that could slow adoption, Mainelli pointed to cost first. “Today, it is cost,” he said. “And the fact that to run some of the larger AI models locally, you need to buy higher-memory configurations.”

Some buyers may still hesitate about Windows on Arm, though he noted that Microsoft, Qualcomm, and the PC vendors have done a lot of work over the last few years to address most of those concerns.

Compatibility issues aside, I can see RTX Spark laptops potentially paying for themselves over time if they can speed up the work of AI developers and creators. Still, with the initial asking price being as “low” as $2,599 for a machine like the Microsoft Surface Laptop Ultra, even the target customer might have reservations.

More products are coming

Looking ahead 12 to 18 months, Mainelli expects more systems based on the RTX Spark platform. He doesn’t see Nvidia and its partners shifting focus away from the premium segment anytime soon, and commercial products could also appear. For now, though, these remain specialized machines aimed at people who already know why they want the combination of unified memory, CUDA, and local AI capability on Windows.

“I’m confident we’ll see additional products ship leveraging the RTX Spark platform in the future,” Mainelli said. “I expect NVIDIA and its partners to remain focused on the premium and potentially commercial segments in the nearer term.”

To be clear, RTX Spark isn’t trying to be the next mainstream Windows laptop. It’s a high-end option for a specific kind of buyer. Whether that audience grows beyond early adopters and developers will depend on how useful the local AI and memory advantages prove in everyday work — and whether that’s worth the cost of entry.

More from Tom's Guide

• I benchmarked Nvidia's RTX Spark: Apple wins the CPU war, but Nvidia's GPU just broke my testing charts
• I’ve been living with Nvidia’s RTX Spark for a week — it’s not a MacBook Pro killer but something much weirder and wildly powerful
• 'They are new to the laptop market': AMD issues a reality check to Nvidia’s RTX Spark and fires a warning shot at Arm

After telling you about my week living with Nvidia RTX Spark, now I can tell you about the laptop housing it. Microsoft’s Surface Laptop Ultra is easily the most powerful Surface to come out of Redmond, and this is a badass-looking utilitarian notebook to match that energy.

The aluminum shell housing all the internals feels satisfyingly ultra-premium, while opening it up reveals that sharp mini-LED display — not as vivid as OLED, but bright, buttery smooth and color accurate all the same. And those ergonomics are stellar with a great-feeling keyboard and a touchpad that can talk back to you with haptics when you do things around Windows 11.

Then there’s the tweaks to Windows 11 itself. Beyond what you see in version 26H2, setting up an agent is now simpler than ever as part of the startup process. And powering all of this is that RTX Spark — turboboosting a lot of those agentic workflows I created to free up my personal time, alongside the moments of creativity in ComfyUI.

On top of that, it eliminates the compromise between either being a good creator notebook or good at gaming, and just giving you the best of both worlds.

Don’t fall for the marketing hype, though. I know Microsoft is welcoming you to “break up with your MacBook Pro,” and inviting the comparison. And across a few stats, Apple does dominate — like battery life, surface temperatures and raw CPU performance. If you came in looking for this, that high price tag will feel like a sharp sting.

But if you understand what this is — a different species of laptop that focuses on beefing up the GPU grunt — then the story changes. This isn’t a MacBook Pro killer. It’s a creator laptop by day, gaming system by night, and a glimpse at the local future of AI.

Microsoft Surface Laptop Ultra: Cheat sheet

• What is it? Microsoft’s new flagship 15-inch workstation laptop, powered by Nvidia’s RTX Spark chipset.
• Who is it for? This is for the high-end creators, AI developers, and PC gamers who want a boat load of power, alongside local agentic AI capabilities in a portable chassis.
• What does it cost? Pricing starts at $2,599. The price of the model I tested is a whopping $5,899.
• What do we like? The utilitarian design feels completely in charge, that magnetic USB-C port is the smartest charging solution I’ve seen in years, it’s an ergonomic joy to use, and the RTX Spark chip obliterates creative workflows and modern PC games, while ushering in a local agentic future for computing.
• What don’t we like? Battery life and CPU performance is underwhelming compared to Apple’s MacBook Pros. And in our lab testing, the Surface Laptop Ultra does fall slightly behind other RTX Spark laptops.

Microsoft Surface Laptop Ultra: Specs

Microsoft Surface Laptop Ultra: The ups

So as I started daily-driving the Surface Laptop Ultra, I was waiting for the moment I started feeling like I missed my MacBook Pro. That moment never came.

Looking like it’s in charge

The first obvious thing you’ll notice is that sharp, uniform design language. This thing looks like it can do some serious work, and you can see all the Surface's attention to the finer details around the frame too.

There is no lip to get your finger in to lift the laptop screen, but it’s simple to do with one hand. The keyboard feels fantastic to use with a nice satisfying tactile click to each key and a soft landing.

That massive haptic touchpad feels graceful across Windows 11, but the tap backs you get from things like snapping windows to the sides of the screen make it a two-way conversation.

And then there’s the magnetic USB-C port — giving you the MagSafe connectivity without the need to give up a standard port. Obviously, you can see from my TikTok below that I loveed it, but I did hear the feedback: what’s the durability when you whip it out vertically rather than horizontally?

Well, after doing that several times, that reduced height of the USB-C male connector means it pulls out just as easily with the connector safely intact. This is a durable solution, and I hope we see this come to phones in the near future!

RTX Spark drags Windows 11 into the agentic era

As I noted in my “week in the life” diary, this laptop is a beast for local AI. Out of the box, Windows 11 makes setting up agents like Hermes or OpenClaw incredibly simple. On top of that, the power-user centric additions to the UI like moving the taskbar to the side and removing all the pointless start menu widgets is a joy to use.

But at its core, it’s that Team Green silicon and full Nvidia CUDA support that gives this a massive advantage. Most open-source AI models are optimized for CUDA first, meaning that with a little reinforcement learning on Hermes, this laptop was able to autonomously manage my email and task list admin — giving me time to make myself breakfast.

As for the performance itself, you can see this advantage at play in generating text and images — all with zero cloud subscription fees.

While the TG lab doesn't normally run these tests (we will going forward), I've reached out to my friends in the industry to ask about these numbers. And the opinion is unanimous: RTX Spark breezes past M5 Pro, AMD Ryzen AI Max 395+ and demolishes Intel Core Ultra X9 in AI token generation.

But to give myself more context, I faced it off with my RTX 5060 Ti 16GB desktop GPU.

I wasn't expecting it to beat a desktop graphics card. The difference in wattage going to each of these chips is insane! However, the Spark does get impressively close here.

Ending the MacBook dilemma

For years, creatives have carried a MacBook Pro for work and a separate system for gaming. Either its a gaming tower at home, a second gaming laptop or a handheld. The Surface Laptop Ultra ends that compromise, and that comes courtesy of the fact that GPU bolted onto RTX Spark is a real monster.

M5 Pro does pull quite a lead in terms of Adobe Creative Suite workloads, but, you can get supreme gaming here. Numbers-wise, this is close to an RTX 5070 gaming laptop, which Apple can only dream of.

Apple's GPU is strong, but it doesn't have the game support that Windows does. Throw in the vast improvements to prism emulation that support anti-cheat software for multiplayer games, and this becomes an enticing option for working by day and playing by night.

Even before any upscaling tech, it’s a night and day difference in the gaming department. Throw in RTX technologies and it’s a runaway victory.

Oh, and that whole other thing MacBooks did well — running as fast both on and off the charger — yea, the Surface Laptop Ultra does that too.

Microsoft Surface Laptop Ultra: The downs

Nvidia’s first foray into an all-in-one chip isn’t without some issues. The laptop’s not the problem, but rather a couple cracks in the armor and defining who RTX Spark is actually for.

The MacBook Pro reality check

A lot of folks came into the RTX Spark launch hoping for it to be a MacBook Pro killer. If you measure by the CPU, creator performance and battery life, it isn’t.

In multi-core metrics, the Nvidia chip in here performs at the top of its class for Windows laptops, but the M5 Pro does peek ahead.

And the same can be said for creative tasks like transcoding video or working across Photoshop or Premiere Pro, as you saw above. It does end the MacBook dilemma as I mentioned above, but if you have a specific use case, you’ll get faster speeds by going for Apple here.

And then there’s that stamina portion of things. Don’t get me wrong — the claim of “all day battery life” is technically true, but Surface Laptop Ultra barely touches the sides of the efficiency of Apple silicon.

When it comes to gaming, at just over 1.5 hours, you can think of your RTX Spark running at full pelt in AAA titles (or AI tasks) lasting just a little bit longer than your standard issue gaming laptop.

The performance overall is impressive (if you know what to do with it…more on that in a bit), but make sure you bring that 140W charger with you.

Popping the hype bubble with a few reality checks

I’ll be upfront. This laptop is not for everyone. An RTX 50-series gaming laptop could do a lot of what you see here, and if gaming isn’t your main focus, a MacBook Pro could be the move.

So let’s get down to brass tacks here with some reality checks on who this is for:

• The big differentiator is unified memory: With one giant pool of memory to share across all the internals, that’s capable of running far larger local AI models than your standard gaming laptop.
• The Nvidia advantage in AI: Thanks to the AI software stack being almost overwhelmingly Nvidia-optimized, you’ll get the fastest local performance of any laptop.
• The PixelSense mini LED display: It's bright and color accurate, but it lacks the pop of OLED RTX Spark options like the Asus ProArt P16 or the HP OmniBook Ultra 16.

Of course, I can talk about this being the everything machine it is, but when you break down the big things that give RTX Spark the edge here in any buying decision, it starts to level the market in your mind and give clarity to who should buy this.

If you are an AI enthusiast/developer, or you’re keen to jump into the field of agentic AI/AI creative, this is the laptop for you.

If you want good gaming on-the-go, a gaming laptop is the way to go.

If you want portable creator performance, the MacBook Pro reigns supreme.

The Spark does touch on all these things, and it does them well. But at those kinds of prices? If you have clear intentions around what work you’re doing but nothing specific in mind for embracing AI agents (as you’ll see from some of our reviews), this is an investment you may regret.

Microsoft Surface Laptop Ultra: Verdict

The Surface Laptop Ultra is a remarkable piece of hardware. The utilitarian design, brilliantly clever magnetic USB-C port and communicative haptic touchpad prove that Microsoft’s hardware engineering is operating at the highest level.

And as it should, because the RTX Spark chip inside is a bit of a breakthrough for the local agentic future of computing, as well as a monster for creators, developers and gamers alike.

But to be clear: this isn’t a MacBook Pro killer. You’ll notice that in CPU and battery life. Instead the sheer force of that chip and unified memory makes it a weapon for pro workloads — housed in a mean-looking chassis.

Nvidia's RTX Spark chip has been my most anticipated product of the year, and now, it's finally landed in laptops. With RTX graphics to power through 3D work, video and even a side of gaming, along with Team Green's CUDA stack to run AI models and agents locally, what better way to show this off than on a creator-focused laptop: the Asus ProArt P16 with RTX Spark.

Carrying on its legacy of being an AI-infused laptop for creatives from the ProArt P16 2025, this ProArt P16 steps up and delivers an even sleeker, lightweight 16-inch machine with greater battery life and an OLED touchscreen (finally) featuring a smooth 120Hz refresh rate. Along with its varied selection of ports, including an SD card reader, this laptop is geared up to be the ultimate portable notebook for photo and video editing, creative work and more.

More than anything, though, the main draw here is its capabilities for running your own on-device AI agent. No subscriptions or prompt fees here, just an assistant that can adapt to your routines (after a few goes). It's wicked to see in action, and while the Asus- exclusive StoryCube and MuseTree apps are fun to check out, I imagine video editors, 3D designers, game developers and coders will go beyond this to take full advantage of this chip, with apps like Hermes Agent. This has up to a whopping 128GB of RAM to power it all, after all!

But it will take a lot out of wallets, and its premium standard won't be worth the creative power it boasts unless you're an AI power user or a 3D creative. It's also worth noting that this is Windows on Arm, meaning apps and games can either run natively or through Microsoft's Prism emulation, so some may not run exactly as expected (even though Nvidia CEO Jensen Huang says "every single application that Windows has ever run" will work). Oh, and it can still get quite loud when put under pressure and a little hot.

While it's certainly one of the best AI laptops, it's no MacBook Pro killer when it comes to pure performance. But when it comes to AI, it shines in a different way.

Asus ProArt P16 (RTX Spark) review: Cheat sheet

• What is it? An elite creator laptop with Nvidia's RTX Spark N1X chip for 3D creative work and local AI tasks.
• Who is it for? Power users looking for a slim, lightweight machine for 4K (and beyond) video editing, 3D graphics work, game design, coding, and to utilize local AI agents.
• What does it cost? Prepare your wallet. The Asus ProArt P16 (RTX Spark) is available for $2,799 in the U.S. at Best Buy and £3,099 in the U.K. at Currys, and that's just the starting prices. Asus' official website notes prices starting at $4,399 / £3,899, but you can find it for less at third-party retailers. For the highest spec? Expect to pay $6,999 / £5,999.
• What do we like? Its superb performance across the board (from speedy local AI tasks to gaming), the still-gorgeous 16-inch OLED display now with a smooth 120Hz refresh rate, battery life that actually lasts and great port selection for creators — all wrapped up in a slick, premium design.
• What don’t we like? This is a huge investment with AI in focus, so know what to take advantage of with this chip. And this can get loud and a little hot when pushed.

Asus ProArt P16 (RTX Spark) review: Specs

Asus ProArt P16 (RTX Spark) review: The ups

The Asus ProArt P16 with RTX Spark takes the wins of its last-gen model and makes some welcome refinements, too, leading to a thin, premium laptop that's made for creativity, AI and some gaming.

Slim, light and ready to move

Look familiar? This should, as the Asus ProArt P16 sports a near-identical utilitarian aluminum design as its predecessor. But this time, it's thinner and lighter than ever, and actually undercuts the MacBook Pro this time.

Coming in at 13.9 x 9.5 x 0.5 ~ 0.6 inches and weighing 3.9 pounds, this is the slimmest ProArt to date, and it's likely thanks to the laptop having just an RTX Spark chip rather than a laptop GPU fitted under the hood, too. Compared to the previous P16, which is 0.7 inches and weighs 4.1 pounds, it's not a major change, but those small tweaks to the design make it that much more portable and easier to slip into a bag. More so than the MacBook Pro now, at 0.6 inches and 4.7 pounds.

It's a premium machine, from the way it looks to the way it feels, while still being subtle enough to use anywhere, whether that be at the office or a coffee shop. To me, it isn't too far off the slick style of a Razer Blade 16, and I mean that as a huge compliment. The ProArt P16 comes in two colorways, including Nano Black and Neo White, and you'll be happy to know the former delivers a fingerprint-resistant finish.

Another highlight is the backlit chiclet keyboard with 1.7mm key travel, which is comfortable and speedy to type on, along with a big haptic touchpad that feels punchy and accurate to the touch. But unlike the last-gen model, there's no DialPad here, which was a handy way to access different shortcuts, apps or functions right on the touchpad. It's a shame, especially for creative tools, which some will surely miss.

A good port selection will always be appreciated, and the ProArt P16 delivers. With three USB 4 ports that support displays and power delivery up to 40Gbps (any can be used for the 140W USB-C charger), one USB-A for peripherals, an HDMI output and even a headphone jack, there's plenty of connectivity here. And it wouldn't be a creator laptop without an SD card reader, so it's a good thing it has one.

It has (RTX) Spark

The Asus ProArt 16's headline event is easily Nvidia's RTX Spark N1X chip, boasting a 20-core CPU and (get this) a 6144-core GPU, thanks to the tensor cores stuffed inside. There is another RTX Spark N1X processor featuring an 18-core CPU and a 5120-core GPU available on more affordable ProArt 16 models, too, which confusingly has the same name. Be sure to watch out for that.

Our review unit comes with the 20-core RTX Spark N1X variant, 128GB of DDR5X RAM and 2TB of storage. With that kind of power under the hood, especially that RAM, it's like sitting on a goldmine. It's the type of high-level specs you'd find on a MacBook Pro with M5 Pro, an Asus ROG Flow Z13 with an AMD Ryzen AI Max+ 395 chip, and even the previous Asus ProArt P16 with an AMD Ryzen AI 9 HX 370 and RTX 4070 GPU (but the latest model now comes with double the memory).

To cut to the chase, it's a beast. It is incredible what a single superchip can accomplish when it comes to complex local AI workloads, handling 3D creative work and playing the latest PC titles at stable frame rates. To have this running in a thin-and-light 16-inch laptop with actual respectable battery life is a huge triumph. Well, the 128GB of RAM on this review unit definitely helps, too.

In testing, though, it's harder to reflect this. Nvidia notes that in many tests, including Geekbench and 3DMark, the numbers don't reflect the performance of the chip. Even in Geekbench AI, Team Green states that the numbers will be obsolete due to deprecated DirectML, and some games couldn't boot (but there was an exciting workaround).

Regardless, here's a look.

Despite the warnings, the RTX Spark N1X still shows impressive high-end figures. Apple's MacBook Pro M5 Pro still wipes the floor, and it's not the strongest when it comes to single-core performance, but there's a significant uplift everywhere else. The last-gen ProArt P16 with its powerful AMD Ryzen AI 9 HX 370 and Asus ROG Flow Z13 with a similar Ryzen AI Max+ 395 chip can't touch multi-core performance, and for creators, our Handbrake test, which transcodes a 4K video to 1080p, shows the ProArt P16 with RTX Spark cuts times drastically.

What about for 3D work? There's no better way of testing this than in games. After playing Cyberpunk 2077 on Ray Tracing: Ultra settings and seeing around 30 FPS at 4K, and bumping that up to 115 FPS with DLSS with frame generation, yeah — this machine can game.

The chips' RTX graphics (and 6144-core GPU) clearly shine, even beating the numbers of a dedicated RTX 4070 GPU in the previous model. How impressive is that? Now, while this P16's UHD+ OLED display is a visual treat for gaming, I prefer performance, so I was often playing games at lower resolutions for those higher frame rates without heavily relying on Nvidia's frame generation.

The ProArt P16 can breeze through anything I throw at it, and for those complex 4K video edits, 3D design or development, this machine can handle it (as it should, considering its price).

But when it comes to working with local AI agents, this is where the RTX spark truly shines (more on this later).

A display for creatives

Asus strikes again with an absolutely gorgeous 4K OLED touchscreen that any creator will appreciate, and I would say it's one of the best touchscreens you can find on a laptop.

The Asus ProArt P16's 16-inch UHD+ (3840 x 2400) OLED touchscreen features all the perks from its last model, including a productivity-friendly 16:10 aspect ratio. You'll find an ultra-bright 1,600 nits of peak brightness (and this shows), an anti-reflective coating, along with a flood of colors and deep blacks in anything you view. For touching up images in Photoshop with a touch and simply watching shows, this screen is a treat for the eyes. Plus, while there's no stylus included, you'll find this screen does support it.

Thankfully, there is one welcome upgrade I'm happy to see: a 120Hz refresh rate with a 0.2ms response time. No more being limited to a 60Hz screen, as the ProArt P16 now delivers ultra-smooth motion. That complements creative work, but it's even better for gaming.

Gearing up for "Avengers: Doomsday," I watched "VisionQuest" on Disney+ and was blown away by the array of bright colors surrounding Vision as a house in a bright green space was being digitally constructed in front of him. As ever, the ProArt P16's OLED display is one to beat.

Battery life that lasts

The Asus ProArt P16 is a powerful machine with an OLED display and plenty of gaming potential. Usually, that translates to the kind of battery life that is in dire need of an outlet way too often, as the best gaming laptops can attest. But that's not the case here.

Using our battery test, which involves web surfing and streaming video at 150 nits of screen brightness, the ProArt P16 with RTX Spark lasted 12 hours and 26 minutes. That's well past a full working day, and an amazing effort from a machine with the power it packs!

No, this is nowhere near MacBook Pro levels of battery life, nor is it close to what Intel's Panther Lake chip offers in the Dell XPS 14 (2026) at over 20 hours. Still, it makes traveling and using the ProArt P16 far more realistic this time around, with enough juice to power through the day and have a little leftover in the evenings.

Asus ProArt P16 (RTX Spark) review: The downs

The Asus ProArt P16 with its RTX Spark N1X has many exciting features, but its price is not one of them. That alone narrows down who this will be for, and you'll want to make full use of its effectiveness in AI to make the most of what you're getting here.

Some limits

I wouldn't necessarily call this a "down," more like a change in perspective. The RTX Spark N1X is built for local AI and agents, and that means running LLMs and the like without limits. No tokens or per-prompt payments; data and automated processes that are yours and work for your routine.

That's an extremely useful tool to have in your pocket. That is, if you know what you want to use it for. For video editors automating time-consuming assembly tasks or finding highlights in long-form cuts, and developers using an agent to write volumes of code, the RTX Spark in the P16 brings that power on the go. For others, they may not have any use for it beyond writing up drafts, finding specific files, summarizing documents or simply having fun with it.

But if you're looking to take advantage of AI, you can see how the RTX Spark N1X can be an effective way of being productive and simplifying tasks you have no idea where to start with.

A great example: I was trying to play Red Dead Redemption 2, but it would crash every time I booted it up. I had no idea what the problem was, so I asked my Hermes Agent to see what was wrong and fix the problem.

It said everything on the setup side looked healthy, and asked exactly what was happening when I launched the game. At that point, I had gone to make a coffee, so the question timed out. But then, Hermes just went deeper into the issue anyway, and came back with:

"I found that RDR2 has been running in Vulkan mode, which is a known issue on the new ARM Blackwell GPU with driver 617.42. I'll switch the API to DirectX 12 in the config, back it up first, and launch the game to test the fix."

And then, voilà! It started running without any problems. It may have taken me a trip to Google, a look through Reddit posts and some tinkering of my own to figure this out, but if something didn't quite work right, I would have just left Red Dead Redemption 2 unplayed.

That's an amazing way to quickly solve a problem. Now, I tried the same with Forza Horizon 6, which kept saying "Invalid Gaming Services Detected" and that I need to update "Gaming Services." Hermes couldn't quite solve that one, but a little tinkering and direction would have pointed it in the right direction.

Asus' exclusive MuseTree and StoryCube apps make a return, too, and these are a great way to start generating and visualizing ideas, plans and even turn simple text or drawings into full-blown videos (like my terribly drawn stickman that turned into an animation). I got more out of Hermes, but these are nice apps to have to express creativity.

With tasks like that, I can imagine making full use of an AI agent to automate tasks and help me here and there, and developers, editors and more could take this even further. But for anything other than AI-focused tasks, there are other laptops out there that have better performance, like the best MacBooks, or that play games better, like the best gaming laptops.

Hot under pressure

It's easy to tell how much power is packed under the hood of the Asus ProArt P16, because you can hear it as soon as an AI agent starts processing a prompt or a game is booted up.

In all fairness, when it comes to general tasks such as browsing the web, writing up documents or watching shows, the laptop is dead silent. But when I started using the Hermes Agent to ask simple questions, the fans start whirring and slowly taking off as it starts to process what's been asked. It's not obnoxiously loud, but I wouldn't call this laptop "stealthy."

I also noticed it getting a little hot towards the keyboard area. That's likely due to the laptop's design, with the keyboard deck drawing in cool air to "maximize fresh air volume inside the chassis." I'd imagine it needs as much cooling as it can get, but this is supposed to keep the keyboard surface "comfortably cool." It's a touch hotter than that when put under pressure, though.

The price of (RTX) power

Yup, the RAM crisis isn't going anywhere. It's $6,999 / £5,999 for the highest configuration of the Asus ProArt P16 with RTX Spark. You can get three iPhone Duos and still have $1,000 left over, seven PS5 Pros at their now-increased price — you get the picture.

Even the base configurations I found, coming in at $2,799 / £3,299, are $500 more than the advanced ProArt P16 we recommended in 2025. And that came with a respectable 32GB of RAM and an RTX 4070! While it's more affordable than a 16-inch MacBook Pro with M5 Pro ($2,999 / £2,999), that still comes with 24GB of RAM and a 1TB SSD (and more performance power, according to the numbers).

Over the past year, we've seen laptop prices skyrocket, and despite not needing a discrete laptop GPU now, the RTX Spark hasn't made this machine any more affordable. This is a prosumer laptop for a niche group of users, and you really have to know what you're going to use this laptop for to invest in it.

Asus ProArt P16 (RTX Spark) review: Verdict

The Asus ProArt P16 is an outstanding laptop for creativity, with its legacy continuing with the might of Nvidia's RTX Spark N1X. With an even slimmer design that's light enough to bring with you anywhere, a knockout OLED touchscreen with amazing brightness and colors, the right ports and battery life that can (finally) get you past a workday and still have juice left, Asus has done its creator laptop justice.

But are you willing to pay a high price for a laptop that's mainly dedicated to AI? That's the main question to ask yourself. For me, I wouldn't be pushing agents to their limits in my day-to-day to justify the high price, despite seeing its perks. Still, running AI models and agents locally is an impressive feat, and I love that this acts as a competent gaming machine to play the latest PC titles, too.

If you know that you could fully utilize Nvidia's CUDA and RTX graphics for creative work and beyond, then this laptop should be calling to you. And no, you won't need the top configuration, unless you're sitting on a very stacked wallet. It's one of the best AI laptops around, and it would want to be at the price it's going for.

The HP OmniBook Ultra 16 ($3,199 to start), like all of the new RTX Spark laptops, occupies a unique position in the laptop space. Designed for on-device AI tasks, it’s meant to facilitate the workflows of folks who work or dabble in that space. In that sense, it’s Nvidia and Microsoft’s answer to Apple’s more powerful M-series Macs for running AI. However, it’s decidedly overpowered for everyday work and relatively underpowered for high-end gaming.

The laptop itself is practically a work of art, thanks to its sleek all-black aluminum design and soft textured surface. The 16-inch 3K OLED touchscreen, roomy lattice-less keyboard, and punchy speakers also lend to this laptop’s premium experience. This is the kind of laptop you want to be seen using.

Like the recently released Googlebooks, RTX Spark laptops like the OmniBook Ultra 16 aren’t for general users. Because of that, you’ll want to seriously consider whether these laptops are for you. To that end, here’s my full review of the HP OmniBook Ultra 16 to help you decide.

HP OmniBook Ultra 16 review: Cheat sheet

• What is it? The HP OmniBook Ultra 16 is a high-end thin-and-light laptop powered by Nvidia’s new RTX Spark chip.
• Who is it for? This notebook is for those who want a high-powered machine for on-device AI work.
• What does it cost? The HP OmniBook Ultra 16 starts at $3,199 at Best Buy. This is the same model I reviewed, and it packs an Nvidia RTX Spark N1X chip, 32GB of RAM, and a 1TB SSD. HP has a higher-end model for $4,999 with 64GB of RAM and a 2TB SSD.
• What do we like? We like the sleek design, gorgeous 16-inch OLED panel, lattice-less keyboard, and strong RTX Spark-driven performance.
• What don’t we like? We don’t like the steep asking price and unimpressive battery life.

HP OmniBook Ultra 16 review: Specs

HP OmniBook Ultra 16 review: The ups

The HP OmniBook Ultra 16 is one of the best RTX Spark laptops around thanks to its solid performance, stellar design, vibrant OLED panel and easy portability.

Lovely design

I won’t mince words — the HP OmniBook Ultra 16 is one of the most beautifully designed laptops I’ve ever tested. This is especially true the instant you hold it, when you can better appreciate its sturdy CNC aluminum chassis with its smooth texture. The all-black color and discreet HP logo on the lid are also quite classy.

Measuring 14.01 x 10.1 x 0.62 inches, the OmniBook Ultra 16 is a lot thinner than you’d expect. That makes it easy to slip into most backpacks. At 4.8 pounds, this isn’t exactly the lightest laptop, but it also doesn’t feel overly heavy thanks to its smart weight distribution.

The trunk hinge design isn’t just for show; it also helps airflow. That said, I like how this design element sets this laptop apart from other clamshell designs. The subtle “OmniBook” etched here is also quite nice.

Typing on the OmniBook Ultra 16 is a joy thanks to the spacious keyboard and lattice-less keys. I’m also a fan of the enormous haptic touchpad, which is just as responsive as the touchscreen. I don’t typically care for laptop keyboards, but the one on the OmniBook Ultra 16 is easily among the best I’ve tested.

You get a pretty decent number of ports for such a thin laptop. The left-hand side has an HDMI port, a pair of USB4 ports, and a headphone jack. Over on the right, there are two USB-A ports and a microSD card slot. Though I wish there were an Ethernet port to complete the package, you get more than enough ports for what you’d need.

Strong RTX Spark performance

Our HP OmniBook Ultra 16 review unit is the entry-level model, which packs an Nvidia RTX Spark N1X processor, 32GB of RAM, and a 1TB SSD. As the first RTX Spark laptop I tested, I was very curious to see how it performed in a variety of situations, including basic everyday work and gaming—along with some local AI testing.

It should come as no surprise that the OmniBook Ultra 16 had no problem handling my average workflow, which typically consists of multiple open Chrome tabs, Slack, photo editing in GIMP, and the occasional YouTube video running in the background. As I said in the intro, this is an overpowered machine for the basics.

Now, how did HP’s RTS Spark laptop fare in our lab testing? As you can see in the chart above, the OmniBook Ultra 16 scored well in the Geekbench 6 single- and multi-core benchmarks. It also turned in solid numbers in the Handbrake SSD test. The Samsung Galaxy Book 6 Ultra, which packs an RTX 5070 GPU and 32GB, didn’t perform as well. However, the 16-inch MacBook Pro M5 Pro outperformed both laptops in these tests.

The OmniBook Ultra 16 also performed well in our Adobe benchmarks, which include Photoshop and Premiere Pro. Despite the strong results, Apple’s MacBook Pro scored better on both tests by a considerable margin.

In gaming, the OmniBook Ultra 16 has mixed results. In our testing, which involves running a game’s built-in benchmarking tool at maximum graphical settings and native resolution, games like Assassin’s Creed Shadows and Cyberpunk 2077 barely hit 20 frames per second, let alone the minimum 30 fps.

Even if the OmniBook Ultra 16 couldn’t match a dedicated gaming laptop like the RTX 5070-driven HyperX Omen 16, it was generally on par with the M5 Pro MacBook Pro, though Borderlands 3 ran considerably better. Though both HP and Apple’s laptops did well in the 3DMark graphical test, it shows that games need to be optimized for the respective silicon to run at their best.

Our gaming benchmark tests are pretty demanding, so you can still have a great gaming experience with the right settings. For instance, Cyberpunk 2077 ran between 38 and 47 frames per second at default graphical settings (no frame gen) at native 1800p resolution. When I dropped the resolution to 1080p and enabled DLSS, the FPS hovered between 58 and 65, which is quite nice!

On-device AI actually works

RTX Spark systems like the OmniBook Ultra 16 are built for on-device (or offline) AI tasks. Since I’m not a coder or programmer, I just did a simple test using Qwen3.8 27B to see how this all works. Here is the prompt I used:

"I have a 48-hour layover in Tokyo with a $300 budget. Plan a realistic, hour-by-hour itinerary for someone who loves ramen and hates crowded tourist spots."

Though it took around 15 minutes, I got a detailed itinerary. I didn’t check it for accuracy since my goal was to see if the laptop could complete this task while offline. Yes, you can get the same results much faster by asking ChatGPT, but the point is that you can safely work with AI offline on a machine like this instead of potentially sharing private information on services that depend on the cloud.

Vivid display

One of the main selling points of the HP OmniBook Ultra 16 is its stunning 16-inch OLED touchscreen. In the latest trailer for The Legend of Zelda: Ocarina of Time, I was stunned by the deep contrasts of both day and night-time scenes. Colors appear appropriately bold, while the 3K resolution and 120Hz refresh rate ensured everything appeared sharp and ran smoothly, respectively.

Our lab tests confirm what my eyes saw. Color reproduction (sRGB and DCI-P3) leans toward the oversaturated end, but not much so. Color accuracy (Delta-E) is also very strong. As you can see, these values are on par with some of the OmniBook Ultra 16’s competitors.

The touchscreen capabilities are on par with other Windows laptops I’ve tested, never failing to register my gestures. I don’t always use the touchscreen on laptops that have them, but I appreciate their inclusion in case I ever feel the need to tap on something.

HP OmniBook Ultra 16 review: The downs

The HP OmniBook Ultra HP is an impressive laptop but it has some noteable flaws.

Steep price

Make no mistake, the HP OmniBook Ultra 16 costs a pretty penny. The entry-level model starts at $3,199, which comes with 32GB of RAM and 1TB. For $4,999, you can get a model with 64GB of RAM and a 2TB SSD. If you want to go all out, the highest-end model for $6,299 comes with 128GB of RAM and a 2TB SSD.

Now, if you’re the target user who wants a powerful laptop for on-device AI workloads and big creative projects, then the price might be worth it. However, if you’re just looking for a traditional work or gaming laptop, then you’re better off looking elsewhere.

Middling battery life

HP says the OmniBook Ultra 16 has up to 17 hours of continuous video playback at 1080p and with the display set to 200 nits of brightness. However, on the Tom’s Guide battery test, which involves continuous web surfing over Wi-Fi with the display set to 150 nits, the OmniBook Ultra 16 endured just eight minutes short of 11 hours.

As you can see, competitors like the MacBook Air M5 and Galaxy Book 6 Ultra outlasted HP’s laptop by well over four hours. Now, we were only able to run a single battery test on the OmniBook Ultra 16, so I’ll update this review after we’ve done three full tests as we usually do. That said, I don’t expect the final results to be greatly different.

While I’m placing battery life as a con, it’s only because we live in a world where Apple, Qualcomm, and even Intel have raised the ceiling on laptop battery life. You’ll be able to get plenty of work done on the HP OmniBook Ultra 16 on a single charge. That said, don’t forget to bring its 140W GaN charger when you’re on the road.

HP OmniBook Ultra 16 review: Verdict

The HP OmniBook Ultra 16 isn’t a laptop for general customers, but it’s great at what it was designed for. If you want a portable device for on-device AI work or creative projects, you won’t go wrong here. The fact that the laptop is a beautiful piece of work only sweetens the deal.

Even if RTX Spark systems like the OmniBook Ultra 16 are only for the pros, they’re impressive machines that prove you don’t need the cloud to get AI work done. If what I said about the HP OmniBook Ultra 16 impresses you and you think it could benefit your work (and won’t completely drain your bank account), then certainly give it a try.

The embargo has lifted on Nvidia's RTX Spark platform, and the internet is currently doing what it always does: arguing over spreadsheet math. I've done something different with my diary of a first week living with Spark, but I've been busy benchmarking too!

For months, the tech industry (myself included) hyped up this Arm-based Grace CPU and Blackwell RTX GPU combo as the ultimate "MacBook Pro killer." Reviewers (also like me) have spent the past seven days squinting at Geekbench scores to see if Nvidia finally dethroned Apple's M-series silicon.

Let me save you some time: it didn't.

But judging RTX Spark purely by its single-core CPU speeds is like judging a Ferrari by its cup holders. And after a week of stress-testing the Microsoft Surface Laptop Ultra with Spark — running every synthetic and real-world test we can throw at it — it's clear that this is so much more.

Those numbers tell a very different, far more complicated story. Let me explain.

Where to buy RTX Spark laptops

• MS Surface Laptop Ultra: $2,599 @ MS Store
• HP OmniBook X AI 14: $2,999 @ HP
• HP OmniBook Ultra AI 16 OLED: $3,199 @ Best Buy
• Lenovo Pro 9n: $2,999 @ Lenovo
• Lenovo Yoga 9n 2-in-1: $2,999 @ Lenovo
• MSI Prestige N16 Flip AI+ OLED 2-in-1: preorder for $3,299 @ MSI
• Dell XPS 16: $3,799 @ Best Buy
• Asus ProArt P14: $6,499 @ Asus
• Asus ProArt P16: $4,499 @ Asus

CPU reality check: Apple is still king, but other Windows laptops don't stand a chance

So let's start with the first benchmark everybody goes to. If you were hoping Nvidia's Arm-based Grace CPU was going to embarrass the M5 Pro, you need to adjust your expectations.

Given how long it took to make this, it's fair to say this was the main bit I felt nervous about. In short, not terrible, but underwhelming.

That being said, this was one of the first chances I had to test Nvidia's claims of getting the same performance on and off the charger.

Now I know there's a difference maker in here — Windows power settings. Putting it to best efficiency will probably starve the chip of power to match it. With that in mind, I've just done the test in both this mode and best performance to see what I get.

Certainly a surprise to see it gain a few points when unplugged, but this falls within the window of variability in the test results I've been getting. So the answer is a resounding "yes," provided you slap on best performance.

To dig deeper into that multi-core performance, I went to Handbrake. One of the tests we run across all systems is transcoding a copy of Tears of Steel from 4K down to 1080p. This is a solid real-world test of video encoding and real-world multi-core processing.

As you can see, it clearly leads the way in Windows laptops (Intel caught napping there), but Apple silicon reigns as champ.

The GPU flex: Comparable to an RTX 5070 laptop

Gaming is where Nvidia gets its lick back against the competition. It has a massive Blackwell RTX GPU in it, after all, and when you look at the 3DMark numbers, it matches up to something you’d see in an RTX 5070 gaming laptop — even when tasked with x86 emulation in some of these tests.

And to check it's not just the CPU getting that same performance on and off the charger...

Once again, same performance on and off the battery. This is consistent with what Nvidia's been telling us, and it's one of the features gatekept by Apple MacBooks that is now in the hands of Windows users!

Now, let's get into the games.

Forza Horizon 6

Forza Horizon 6 is one of my favorite racing games of the past decade, so it only makes sense I start here. Let's max it without DLSS tech and see what we get.

Bear in mind this is a stress test of epic proportions, but you can see how it struggles. That 1% low is a good indicator of the consistency of the frame rate, which is highly volatile here.

Interestingly, as I tried this push to Extreme + RT settings, I noticed some rubberbanding in the gameplay — probably down to the CPU having to work overtime translating the x86 code of the game while also sending the instructions to the GPU.

You can see that as Frametime spikes can be seen anywhere from 60ms up to 140ms. The game feels sluggish.

But now let's hone it. Thinking about this like an RTX 5070 laptop, I'll drop it down to Ultra + RT (same resolution) and stick with DLSS 4.5 set to auto with dynamic frame generation.

Immediately, this feels so much better to play! There are still some latency spikes here and there, but none that are hardly noticeable.

Also interesting to note, the temperatures on the GPU dropped too by one degree (71 C in the first run, and 70C in the second).

And the cherry on top — here's performance on battery.

Yep, same performance on and off the charger here!

Cyberpunk 2077

Listen up, choombas! It wouldn't be an Nvidia laptop test if we didn't touch on Cyberpunk 2077. For context on this one, I'm gonna compare it against gaming laptops with different GPUs, so you can see where it lands.

And if you're curious, I got 38.9 FPS when unplugged (basically 39).

Black Myth: Wukong

Is this a safe space? ...I'm really not a fan of Black Myth: Wukong.

OK, I get it! I can appreciate the craft of it, and I get why people love it. I've just never got on with it. That being said, I did benchmarks for this too.

...you spotting a pattern? This maxed-out RTX Spark is lining up pretty much neck-and-neck with the RTX 5070, while also running cooler and more efficiently. Nifty!

Gears of War: E-Day

This came out recently, and I saw it being played at the Surface Laptop Ultra event in San Francisco, so of course I had to push it further here.

This is running at 2180x1453 Ultra settings with DLSS 4.5 Dynamic and RTX Mega Geometry turned on.

Some observations here — this is clearly a scalable engine on PC that can run fast here. But there were some micro-stutters when I pushed it to the bleeding edge.

That being said, the average frame time and response to controller inputs meant this all felt smooth with virtually zero latency.

Creative apps is where RTX Spark starts to shine

There are several ways to test creative performance, so I'll dive into them one by one. PugetBench is a good way of seeing how a laptop will fare in your standard creative prosumer workload across Photoshop and Premiere Pro. Here's how RTX Spark fared in my testing.

The finely-tuned cores of the M5 Pro take the win here, but RTX Spark does take a leap ahead of its Windows competition in creator performance.

Let's get to Cinebench

Unfortunately, there isn't any GPU testing available here yet (the OptiX driver for the chip isn't there), so this is a straight CPU comparison.

These numbers put it ahead of Intel, AMD, and Qualcomm's latest flagships, but Apple M5 Pro (again) comes out on top. It's the best of the Windows bunch.

AI performance is where RTX Spark takes the lead

To put some numbers to Nvidia's advantage here, I ran it through UL Procyon AI benchmarks.

This isn't a test that has been normally run on other laptops in the Tom's Guide lab, so I've had to ask around my friends/fellow nerds for insights on this.

In their experience, RTX Spark seems to be surpassing the M5 Pro's AI prowess, exceeding the capabilities of AMD Ryzen AI Max+ and blowing past Intel Core Ultra X9. Once I can do these tests myself, I'll do a follow-up.

Also, for what it's worth, here's the comparison to my RTX 5060 Ti 16GB desktop GPU.

A reduction is always expected between the raw wattage of desktop parts and a laptop chip, but the Spark does get impressively close.

Battery life is a mixed bag

So what about stamina? Nvidia promised all-day battery life, and technically that’s true. But it doesn’t come close to the efficiency king of Apple’s MacBook Pro.

When it comes to gaming or running local AI at full pelt, this falls in line with what you’d expect from an RTX gaming laptop (our gaming test result got one hour and thirty-eight minutes) — give or take about 20-30 minutes depending on how much power the internals soak up.

Meanwhile, if you're expecting that same all-day battery life claim to extend to gaming, that's not the case. You do indeed get more stamina than your average gaming laptop, but not by much.

Who should buy RTX Spark, and who should buy a gaming laptop?

That battery equivalency does raise another question — who is RTX Spark for?

Because for all intents and purposes, an RTX 50-series gaming laptop could do a lot of this workload, whether it’s gaming, creative work, or some of the local AI stuff. And depending on how efficient that gaming laptop can run, you could get a similar battery life.

The real differentiator comes in that unified memory. With there being two pools of memory between the RAM and the GPU’s VRAM in a gaming laptop, it’s not as efficient as having one giant tub of it that can be divided depending on job priority.

That means on RTX Spark, you can run vastly larger local AI models, and larger projects in the likes of Blender than you could elsewhere. This is definitely for the prosumer market.

More from Tom's Guide

• I didn’t believe an Nvidia RTX Spark laptop would have the same performance both on and off the charger — so I put it to the test
• Forget RTX Spark: The Surface Laptop Ultra’s magnetic USB-C charger is a game-changer that makes Apple’s MagSafe look obsolete
• I just tested Windows 11 26H2 — here’s how to update now and why Microsoft finally fixed the two worst things about Windows 11

Let me be clear from the top. If you are looking for the raw benchmark data, the thermal charts and synthetic scores for Nvidia’s RTX Spark, you can head over to my testing lab here.

…ok are all the speeds and feeds people gone? Good, because while I’m over there doing the math, and everyone else on the internet combs over the numbers, data doesn’t explain what it actually feels like to use a machine with a locally hosted AI brain.

You have to unlearn years of cloud-tethered habits (like relying on a browser-based chatbot tab) and start treating your operating system like an overly eager digital intern. And over the past few days, I found this out and quite frankly, it’s a bit of a breakthrough.

So, before you dive into the frame rates, here is a diary of my first week ditching the M5 MacBook Pro, and living exclusively on an Microsoft Surface Laptop Ultra with RTX Spark (and 128GB of unified memory).

Day 1: The Sims 4 disaster (and a lesson in patience)

I returned from the Surface Laptop Ultra event in San Francisco pretty late, but I didn’t feel tired. I was caught up in the excitement of tearing this machine out of the box and seeing what it could do.

And my first test? Nothing to do with productivity. Instead, I installed Hermes agent with Qwen 3.8 Flash Next to play The Sims 4 — build a house and get a job.

Now with that out the way, this first test did not instill me with immediate confidence in Nvidia’s vision of a local agentic future. The AI fumbled around, got lost in the house building menu, and when I got it to the point of having a home roughly three hours later, it managed to start a kitchen fire.

Throughout that time, my prompts to the agent grew more frustrated, and it repeatedly made the same mistakes — forgetting that the graph of co-ordinates keeps moving with the character in the center of the screen and going round in circles.

But watching it stumble taught me a crucial lesson in reinforcement learning. No, not that reinforcement learning that's the complex phase of training an AI model that researchers work hard on. This is more in the human, psychological sense — rewarding good behavior and correcting bad behavior in real-time.

I had another go in the morning with a calmer head, continued to tell it when it was doing the right thing, encouraging it to keep going and we made it to the first gym.

You see, interacting with a local agent isn’t like querying a search engine or talking to a cloud frontier model; it’s exactly like playing two-player Portal 2 with my eight-year-old nephew. You can’t get frustrated when he jumps into the water and dies for the 5th time. You have to give him the carrot, not the stick — guide with positive reinforcement and structured boundaries.

Once that clicked in my mind and my behavior changed, learning how to actually “parent” the agent immediately skyrocketed the output quality. And that’s when I truly got to work.

Day 2: The butler arrives

By the next day, I booted up the Hermes agent and built a set of custom skills. I hooked it directly to my personal Google Workspace API, and for my Tom’s Guide account (Future locks down API access pretty tightly), I set up a script allowing it to physically operate my browser.

I named it Jeeves, and every morning, I just write “check-emails” and it gets to work across both accounts — reading my inboxes, deleting anything unnecessary (like marketing emails or phishing scams), drafts surprisingly human responses to those that are important, and generates a prioritized to-do list for my workday based on emails and Slack.

Now I know what you’re thinking. Isn’t this possible on other machines? Yes. Hermes is an agentic machine that works across Macs and other Windows PCs too (including AMD machines and we all know how they feel about the RTX Spark hype).

But Nvidia’s GPU is the key advantage here, and it comes down to CUDA (which stands for Compute Unified Device Architecture). Basically, it's a technology that unlocked the power of the GPU for other purposes (like AI in this instance).

It’s the reason why Team Green is the biggest picks and shovels company in the cloud AI gold rush (or bubble…however you see it), and an overwhelming majority of open-source models used for local AI (including the Qwen model I’ve been using) are built, trained and initially optimized specifically for Nvidia’s CUDA platform.

There’s a noticeable speed advantage in AI between RTX Spark systems and trying Hermes Agent on my MacBook Pro. On top of that, you're seeing Spark lead substantially against Ryzen AI Max+ 395 (I haven't had access to test 495 PRO).

I’m getting into the weeds here, the difference maker here comes down to my awful work-life balance. I usually sleep with a laptop next to me (...awful, I know), and when the alarm goes off at 8am, I’m right back on my MacBook checking emails and figuring out what to do that day.

Now, I can just throw my agent at it, go make breakfast and coffee and chill out talking to my wife before the day begins at 9am. It’s these small but significant time saves that I feel are the most important.

Day 3: Embracing the creator chaos

Mid-week, I dove into content creation. This is kind of the RTX Spark’s bread and butter, because while the Arm-based Grace CPU has noticeably slower single-core speeds compared to the current heavyweight champions over at Apple, its multicore performance is a runaway freight train.

Throw in that massive Blackwell GPU, and I was having a ball blasting through a project on an open-source creative suite.

Then, I tackled ComfyUI. At first glance, the node-mapping interface is a chaotic, terrifying mess of digital spaghetti. But after a day of tinkering and reading guides, the logic clicks. My first challenge: ask my wife to send me a quick sketch. She doodled a picture of Medusa, which I fed into the local UI.

Within 20 seconds, the RTX Spark chewed through the local rendering and spat out a 90s-style cartoon image of her drawing. Then going a little over the top, I went further with an image-to-video pipeline and made a Saturday morning cartoon-style scene of Medusa turning a man into stone.

The speed differentials of this are massive, and one of the jewels in the RTX Spark's crown — roughly 2-3 seconds faster per image generation in my UL Procyon testing against AMD Ryzen AI Max+, and the MacBook Pro trails too.

I’m no fan of AI slop, but credit where credit’s due. Doing this with a cloud AI model would have cost a premium subscription, and without the finite controls of ComfyUI, it would have taken a lot longer to get the results just right.

Day 4: Mutating code and webcam magic

I’ve got distracted enough by AI. Now it’s time to do the thing that I love — gaming. And being honest, playing on RTX Spark is generally excellent. Turns out the fix to gaming on Arm systems is to just throw a massive GPU at it.

007 First Light runs at 1440p with everything turned up to Ultra, DLSS 4.5 and Dynamic Frame Generation maxes out the refresh rate on this laptop screen, DLSS 5 on NBA 2K27 is still as photorealistic (and divisive, looking at my comments) as ever, and shooters that require low latency rapid reactions run smoothly on here (complete with anti-cheat support).

But there are still some gremlins in the system. Red Dead Redemption 2 hit a brick wall by throwing an incompatibility error and refusing to run.

After speaking to Nvidia, I got a guide to make it run on DirectX 12 rather than Vulkan, which didn’t work through the physical steps given to me. So rather than search Reddit for an answer, I simply asked the Hermes agent to make it work.

The local AI dug into the file director, literally rewrote the offending configuration code to bypass the Arm translation block, and the game booted up. Having your laptop dynamically rewrite the game code to fix its own compatibility issues feels like pure sci-fi.

I also had meetings to go to, so I fired up the new version of Nvidia Broadcast, which is basically DLSS for webcams. This 1080p 30 FPS shooter can embrace that GPU prowess to upscale to 4K60 with a studio light — cleaning up the muddy laptop camera feed in real-time. My team really noticed the difference!

Day 5: The MacBook Pro reckoning

By the end of my first week, I had to face the reality of the silicon and hardware encasing it.

Going into this, everyone — Microsoft (with that $1,000 trade-in offer), tech journalists, and myself included — came in thinking the RTX Spark could be the ultimate MacBook Pro killer. The truth? It’s not.

In my standard browser run-down test, the battery died right around the 10-hour mark. That’s solid for a Windows machine and does fit Nvidia’s claims of all-day battery life, but it isn’t touching Apple’s endurance. Furthermore, Apple’s M5 Pro and Max chips easily outstrip the CPU speeds of this system.

But I realized that comparing it to a MacBook Pro misses the point entirely. The RTX Spark isn’t trying to be a better Mac; it is a different species of computer that has arrived early.

It is a statement of intent from Nvidia about where computing is going — trading raw benchmarking crowns on the stats that we currently see as important for the ability to carry a self-rewriting, fully autonomous, CUDA-accelerated digital brain in your backpack.

It requires a new set of behaviors, but once you let local AI take the wheel in some areas, it makes you believe the future of computing is entirely local (and without a subscription fee).

More from Tom's Guide

• I didn’t believe an Nvidia RTX Spark laptop would have the same performance both on and off the charger — so I put it to the test
• Forget RTX Spark: The Surface Laptop Ultra’s magnetic USB-C charger is a game-changer that makes Apple’s MagSafe look obsolete
• I just tested Windows 11 26H2 — here’s how to update now and why Microsoft finally fixed the two worst things about Windows 11

Last week, AMD fired a warning shot at Nvidia’s RTX Spark. Today, Team Green’s payload has arrived. Ahead of the highly anticipated October 16 launch, Nvidia just unleashed a tidal wave of software for its audacious Arm-based chip, the massive Blackwell RTX GPU.

They aren’t just selling a new chip; they’re trying to prove that their garden of software features makes the jump to Arm completely worth it.

And on top of that, I currently have the Microsoft Surface Laptop Ultra with RTX Spark sitting on my desk (actually typing this story on it right now). Now, before I lock myself in my lab for the review, I want to know exactly what you want to see this thing do.

Here is the cheat sheet of the craziest software witchcraft Nvidia just announced. Read it over, drop your most chaotic testing requests in the Q&A box just below, and I will push this hardware to the absolute limit.

Reminder: We’re a friendly bunch, and this community is a safe space for anyone who wants to learn about RTX Spark. Please treat everyone (including me) with respect and avoid any nasty language.

AI without the computer science degree

Running a Large Language Model (LLM) on your PC used to require opening terrifying command-line terminals and pretending you knew how to code (I’m guilty of that one with my D in Computer Science). That friction is well on its way to being killed, and Nvidia is taking another big step forward.

• Hugging Face Llama Windows: Available today is a free, idiot-proof Windows app that lets you download and run local AI models with a standard graphical interface.
• Nvidia PAIR: Now out of beta, this free, open-source tool can essentially turn your home into its own AI data center — allowing PCs and MacBooks to share AI compute across a local network. Basically, if your prompt needs more horsepower, it can find some from your desktop in the other room.
• Getting agent-ready: New skills are coming online so your AI agents in Hermes, OpenClaw, and Perplexity can use Nvidia’s apps (Broadcast, RTX Remix, etc.).

Also, Nvidia Broadcast is getting a big upgrade with RTX video super resolution and frame generation—both for webcam and offline file processing.

The “Nemotron” Intern

On October 15th, Nvidia is dropping the Nemotron 3.5 Bolt 74B A9B model. That’s a whole lot of words, but this is basically an improved key to agentic AI.

This is a “mixture of experts” AI agent built specifically to fit inside 24GB of memory on the RTX Spark — running constantly in the background, writing code, doing research, and monitoring apps autonomously.

Skyrim NPCs that actually talk back

That Nemotron model style has a different use too — making game NPCs have personalities. Nvidia’s built a smaller, ultra-responsive model called Nemotron 3.5 Bolt E4B (again, more alphabet spaghetti), but on October 23rd, you’ll see what this can do in SkyrimNET.

Basically, this is an AI NPC mod for Elder Scrolls V, where instead of clicking through pre-written dialogue trees, you can literally talk into your microphone, and NPCs will generate dynamic, context-aware conversations and reactions on the fly.

I can’t wait to gaslight Nazeem with this…

DLSS 5 just found another gear (and a new cheat code)

Nvidia’s DLSS 5 has split opinions in NBA 2K27 (I see you in the comments). In my mind, this 3D-guided neural rendering model works well in photorealistic games — but maybe leave it off in more artistic ones.

But on October 16th, it’s set to get a speed boost with a more efficient model that Team Green claims will push frame rates up by an additional 1.4x over what I tested. Oh, and for the millennial-coded individuals out there, Hogwarts Legacy is getting the DLSS 5 treatment in November.

Over to you: Build my benchmark hitlist

Nvidia is making massive promises about Arm-based gaming, offline AI agents that don’t charge you a cloud tax, and real-time AI video game characters. AMD claims this whole platform will falter under the weight of Windows emulation.

I have the hardware. I have the games. I have the local AI models. Let’s see what this thing can do together.

Now, while I can do plenty of testing and report on my findings soon, some of this won’t be available for a little while. So this will be an ongoing thing as models and updates become available.

More from Tom's Guide

• I didn’t believe an Nvidia RTX Spark laptop would have the same performance both on and off the charger — so I put it to the test
• Forget RTX Spark: The Surface Laptop Ultra’s magnetic USB-C charger is a game-changer that makes Apple’s MagSafe look obsolete
• AMD just flaunted its own 192GB monster chip to spoil Nvidia’s RTX Spark party — Ryzen AI Max+ Pro 495 should worry Apple, too

Nvidia has just properly unveiled RTX Spark alongside Microsoft’s flagship Surface Laptop Ultra, heralding what Jensen Huang said about reinventing the PC — massive unified memory, local AI and desktop-class power in a portable chassis.

If you ask AMD, however, Nvidia didn’t invent a new category. Instead, it validated one Team Red has been selling for over a year. Speaking directly after the RTX Spark reveal, Mike Nordquist, CVP of Client Product Marketing, didn’t hold back with me.

Between calls to celebrate industry competition and pointed critiques of Nvidia’s hardware architecture, Nordquist laid out a sharp, pragmatic case for why AMD believes its second-generation Ryzen AI Max 400 series (codename Gorgon Point Halo) leaves Nvidia’s new darling in the dust.

Editor's note: This interview has been edited for brevity and clarity.

'Nvidia is just getting started'

While Nvidia embraces the unified-memory laptop, AMD was quick to point out that it kicked off this exact architecture with Strix Halo back in early 2025.

“The exciting part is just the category development. We introduced a similar product in early 2025, so having more people come in and validate that, and you see Microsoft beefing up, I think that’s good overall. Competition is good overall,” Nordquist commented.

“We’re in our second generation that we just announced in the last month, which brings 50% more capacity [than RTX Spark]. So you can get higher capability [AI] models than maybe what you saw today.”

This cuts straight to the core of one thing AMD does have an advantage over Nvidia on — core memory. RTX Spark caps out at 128GB of unified memory, but AMD’s Gorgon Halo pushes that ceiling to 192GB. As Nordquist says himself, that gives you “bigger models up to 300 billion parameters,” which ensures a “higher quality.”

The elephant in the keynote: why did nobody say “Arm”?

Quick explainer to kick this off. AMD and Intel CPUs are built on an x86 architecture — the architecture that’s been used by Windows PCs for over 30 years. It has its down sides, but the main strength here is its the default native standard. It’s been around for ages and chips are built for it.

Nvidia’s RTX Spark and Snapdragon X Elite use an Arm architecture. Arm’s not new, but comparatively, it’s the new kid on the block which does introduce some power efficiency gains.

However, it’s main issue is emulating these apps built for x86 into Arm. There’s a performance penalty there, as it needs to translate the code as you use the app at the same time.

This is probably the sharpest jab from Nordquist. Not about raw AI performance or memory bandwidth, but the glaring omission in Nvidia and Microsoft’s keynote. Across the entire launch, the word “Arm” was practically scrubbed from the script.

“Everything just runs native [on AMD], and I still don’t know what that experience is going to be, how great the CPU is going to be,” Nordquist pondered. “We feel really good that everything just runs out of the box with out product. And I think those questions remain [with RTX Spark].”

When pressed on whether Windows on Arm is finally staging an unstoppable coup against traditional x86 computing, Nordquist dismissed the supposed architectural superiority of Arm outright.

“I don’t think there’s anything magic about going to Arm — that it’s going to be lower power or some other attribute out there. I don’t think we’ve ever believed that, and I don’t think Intel probably believes that as well,” Nordquist responded.

“I didn’t hear Arm mentioned once. It was interesting in their keynote that neither Nvidia nor Microsoft talked about it.

Thirty years of laptop DNA vs a GPU giant’s first clamshell

Nvidia might dominate AI data centers and even make the dedicated GPUs for gaming laptops. But when it comes to the messy, compromise-heavy reality of consumer laptops — thermal throttling, battery curves, sleep states and legacy software — Nordquist hammered how that building a standalone laptop platform is a different beast.

“They’re new to the laptop market in general. We’ve been doing it for 30 years-plus in this space, so I think we know how to run Windows,” Nordquist added.

“There’s no emulation; the games are just going to run natively. You’re buying into something that’s going to work, and not having to worry about whether something’s going to break. You’re just kind of covered with what we have.”

The silicon war moves to the bench

Nordquist’s retort lands with some weight because it exposes Arm’s hurdles and the challenge Nvidia has:

• The compatibility tax: Microsoft has worked hard on its Windows Prism Emulation layer for translating x86 apps to Arm, but running that translation still risks edge-case performance hits. Conversely, AMD’’s x86 architecture guarantees zero translation overhead for hefty software and native PC gaming.
• The memory ceiling: Nvidia’s 128GB unified cap is undeniably impressive, but AMD’s 192GB ceiling gives local AI 50% more breathing room for more concurrent agents.
• The category reality: Nvidia’s joined a party AMD rocked up to a year ago. The company has already spent 12 months taking consumer feedback and refining the second-generation silicon.

But ultimately, the time for talk is over. Nvidia brought serious star power, but AMD isn’t blinking. Now it’s time for real-world benchmarking to see whether Nvidia’s Arm silicon can actually match AMD’s battle-tested x86 brute force.

More from Tom's Guide

• I didn’t believe an Nvidia RTX Spark laptop would have the same performance both on and off the charger — so I put it to the test
• AMD just flaunted its own 192GB monster chip to spoil Nvidia’s RTX Spark party — Ryzen AI Max+ Pro 495 should worry Apple, too
• I just tested Windows 11 26H2 — here’s how to update now and why Microsoft finally fixed the two worst things about Windows 11

So Nvidia’s RTX Spark is officially here, and Team Green is making a big stink about its mission to “reinvent the PC” in the age of local agentic AI. But can I be honest with you, dear reader? The AI stuff is cool, but it's also fixing this one key gripe with Windows laptops, which has me believing in this reinvention.

As the headline gives away, I’m talking about getting the same performance both on and off the charger. The snail’s pace I’d get on a Windows laptop whenever it's disconnected has become a commonplace gripe of mine — so much so that I was suspicious of whether Nvidia had actually cracked it.

Well, turns out the company proved me wrong royally with some key examples over the months, showing just how efficient this is with that battery to deliver the same speeds no matter where you are.

The accident

Probably the most surprising view of this potential is in Blender. For those out of the know, this is a seriously intensive app for 3D animation and digital art — it demands a lot of your CPU and GPU in remapping pixels every time you move an image.

During IFA 2026, I saw a Blender demo that was supposed to show the app with and without DLSS activated on two identical Surface Laptop Ultras. Instead, it revealed the raw stamina of an RTX Spark system because one was left unplugged.

Speaking to Nvidia, the demo had been turned on/setup at 9 am, and I attended it at around 2:30 pm. After 5.5 hours, the 10% battery warning had only started showing.

Even on something super power-efficient like a MacBook Pro, you’d be lucky to get 4-5 hours out of it. So you can imagine how blown away I was in this situation.

On top of that, I saw Unreal Engine 5's biggest sample map running on the MSI Prestige Flip N16 without any stuttering off the charger.

No more gaming frustration

And since this is Nvidia, we have to talk about gaming. You already know the key gameplay specs here — DLSS 4.5 supported through the sheer heft of all those Blackwell GPU cores and the horsepower to run 1440p games at buttery-smooth frame rates.

Nowhere was this more obvious than with the Microsoft Surface Laptop Ultra. That magnetic USB-C port may have stolen my heart, but at the same time, I got to see Gears of War: E-Day (a game that's being translated to work with the silicon) run at exactly the same frame rate.

That standard gaming laptop frustration of watching your FPS dip is a thing of the past here. No more massive cut in performance!

What does this mean for battery life?

But let’s get real here. What is the battery life in reality? All of this sounds great, but there isn’t anything concrete beyond a claim of “all-day battery life.”

Throw in the fact that this is an Arm chip and that emulation isn’t necessarily the most power-efficient way to run apps, and this is something I’m very keen to test.

More from Tom's Guide

• NVIDIA RTX Spark laptop preorders are live: here's where to buy them
• AMD just flaunted its own 192GB monster chip to spoil Nvidia’s RTX Spark party — Ryzen AI Max+ Pro 495 should worry Apple, too
• I tried Microsoft’s new haptic Surface Mouse — and standard mice now feel completely broken

The Microsoft Surface Laptop Ultra is real and promises to be a powerhouse. Powered by an Nvidia RTX Spark chip, this 15-inch laptop is built for local AI and 3D graphics. Though its starting price of $2,599 is steep for average users, “prosumers” could certainly benefit from what this laptop aims to deliver.

Of course, this raises a question for the folks the Surface Laptop Ultra is marketed to: why shouldn’t you get a MacBook Pro instead? It’s a fair question, especially since Microsoft wasn’t shy about comparing its latest laptop to Apple’s flagship notebook during the Microsoft Surface event. Jensen Huang says Nvidia and Microsoft have “reinvented the computer as we know it,” but can the Surface Laptop Ultra do anything the MacBook Pro can’t?

While we haven’t yet had meaningful hands-on time with the Surface Laptop Ultra, we have enough information to make some preliminary comparisons between the devices. So, should you get the Surface Laptop Ultra or a MacBook Pro M5 Pro? Read on for all the details!

Microsoft Surface Laptop Ultra vs. MacBook Pro M5 Pro: Specs

Microsoft Surface Laptop Ultra vs. MacBook Pro M5 Pro: Price

Though the Surface Laptop Ultra isn’t as expensive as we feared, even the entry-level model commands a steep price—comparable to the M5 Pro MacBook Pro.

Over on Microsoft’s online store, you can buy the Surface Laptop Ultra starting at $2,599. This model packs an RTX Spark N1X chip with a 5120 GPU and 18-core CPU, 24GB of unified memory, and a 512GB SSD. You can pre-order it now and get it as soon as October 16. Interestingly enough, you can trade in your MacBook Pro and get up to $1,000 cash back on the Surface Laptop Ultra.

The next model, which packs the more powerful RTX Spark N1X chip with a 6144-core GPU and a 20-core CPU, along with 32GB of memory and a 1TB SSD, starts at $3,699. The product page lists various configurations, with the highest-end model, featuring 128GB of RAM and a 1TB SSD, costing an eye-watering $5,899.

Conversely, the 14-inch MacBook Pro with the M5 Pro chip packing a 15-core CPU/16-core GPU, 24GB of unified memory, and a 1TB SSD starts at $2,499. The 16-inch model starts at $2,999 with the same M5 Pro chip, memory, and storage.

For $200 more, you can get a 14-inch model with an M5 Pro chip featuring an 18-core CPU and a 20-core GPU. If you have money to burn, you can configure the 14-inch MacBook Pro with an M5 Max chip (18-core CPU/40-core GPU), 128GB of RAM, and a 2TB SSD for $6,699. This laptop can top out at $9,699 if you get an 8TB SSD.

To be clear, both the Surface Laptop Ultra and MacBook Pro are pricey machines and can get even more expensive when you opt for higher-end components. Yes, the MacBook Pro can shatter your bank account, but if we just look at starting prices, Apple’s powerful notebook is $100 less than Microsoft’s.

Microsoft Surface Laptop Ultra vs. MacBook Pro M5 Pro: Design

Our own Jason England went hands-on with the Surface Laptop Ultra at Computex and got another look during Microsoft’s Surface event. He says the 15-inch laptop feels as premium as a MacBook Pro, with a similar-feeling keyboard and a massive touchpad. Based on what I saw during the livestream, you could certainly mistake the Surface Laptop Ultra for a MacBook Pro.

Getting into some specifics, the Surface Laptop Ultra measures 12.9 x 9.4 x 0.7 inches and weighs 4.4 pounds. Jason says the laptop is “impressively light” and that it has good weight distribution when you hold it. As with the MacBook Pro, it’s easy to open the Surface Laptop Ultra’s lid with one hand.

One of the most interesting features of Microsoft’s laptop is that, according to Microsoft, it has the world’s first built-in magnetic USB-C charging port. While I won’t dispute that, it’s clearly inspired by Apple’s MagSafe charger on MacBooks. According to Jason, the USB-C port survives the trip test.

Since the 14-inch MacBook Pro measures 12.31 x 8.71 x 0.61 inches and weighs 3.4 pounds, it’s smaller and lighter than the Surface Laptop Ultra. However, the Microsoft laptop is smaller and lighter than the 16-inch MacBook Pro, which measures 14.0 x 9.7 x 0.6 inches and weighs 4.7 pounds.

Microsoft is clearly inspired by the MacBook Pro, which isn’t a bad thing given how Apple’s laptop is arguably the gold standard for premium notebook design. So in that sense, both are likely equal here, though we’ll want more hands-on testing before rendering a verdict.

Microsoft Surface Laptop Ultra vs. MacBook Pro M5 Pro: Display

We didn’t get a lot of info on the Surface Laptop Ultra’s display, but it seems to have the basics of what you’d expect from a premium laptop. As with design, it also seems this laptop’s display will be comparable to that of a MacBook Pro.

The Surface Laptop Ultra has a 15-inch PixelSense Ultra touchscreen display, which is a mini-LED. It has a screen resolution of 3270 x 2180 pixels, an aspect ratio of 3:2, and a refresh rate of up to 120Hz. I know those are a lot of numbers, but even without having gone eyes-on with it, I can tell that this display should deliver a sharp and vivid image.

Conversely, the 14-inch MacBook Pro M5 Pro has a 14.2-inch Liquid Retina XDR display (Apple’s name for mini-LED). It has a sharp 3024 x 1964 resolution and a smooth 120Hz refresh rate. Even if it’s not an OLED panel, I’ve always found the image quality pleasing to the eye, with the bold colors and nice contrast levels.

We’ll need to get the Surface Laptop Ultra into our testing lab to see what it can do, but given how it’s mini-LED like the MacBook Pro, I expect excellent image quality overall.

Microsoft Surface Laptop Ultra vs. MacBook Pro M5 Pro: Performance

Microsoft is promising a lot with the Surface Laptop Ultra, at least for developers, creators, and AI engineers. The Nvidia RTX Spark chip powering the laptop has up to 6,144 GPU cores, an Nvidia Grace CPU with up to 20 cores, and up to 128GB of unified memory. Thanks to that, Microsoft says it can run AI models with more than 120 billion parameters locally, with up to 1 petaflop of AI performance.

When Jason tested the RTX Spark itself, he said there’s a lot to gain from the massive local models that can change how you interact with your computer — from it being a tool that lies idle when not in use to an active assistant. This was a point Microsoft kept coming back to during the Surface event. If you’re someone who feels constrained when using laptops not expressly built for local AI, the Surface Laptop Ultra and other RTX Spark machines could be a huge game changer.

Given the power of Nvidia’s chip, it should also be a gaming powerhouse. During the event, we saw a brief glimpse of Gears of War: E-Day running at 60 frames per second. I was able to wring better performance from this game when I played it on the RTX 5080-powered Razer Blade 18, with frames in the 120s. Still, I won’t complain about games running at 60 fps. I expect games can run even better when specifically optimized for RTX Spark.

The 16-inch MacBook Pro M5 Pro I tested is among the most powerful laptops ever. In nearly every metric, it far exceeded the competition — as you can read in my full MacBook Pro M5 Pro review. I can’t vouch for its AI capabilities since I didn’t run any local models during testing, but given that many folks use MacBook Pros to run LLMs locally, it’s a solid machine for that purpose. It can even run graphically demanding games as well as some dedicated gaming PCs, so long as those games have been optimized for Apple Silicon.

Microsoft Surface Laptop Ultra vs. MacBook Pro M5 Pro: Outlook

I’ll need to fully test the Microsoft Surface Laptop Ultra before deciding whether or not it’s better than a MacBook Pro. However, based on what we know, I have an idea of who this machine is and isn’t designed for.

If you mostly use laptops for browsing the web, watching streaming videos, and light work in Google Docs, neither laptop is for you, as they’re way overpowered and overpriced for your needs. If you want a laptop for the basics, the $799 Dell XPS 13 or $699 MacBook Neo won’t let you down, as both are reasonably priced and have premium-like features.

What about if you’re a gamer? It’s still too early to see how games run on RTX Spark systems in general, but if that’s your primary focus, then you’re likely better off with one of the best gaming laptops or even one of the best gaming PCs, especially with how much the Surface Laptop Pro can cost. And given how Macs don’t yet enjoy the same robust gaming support as PCs, the same applies there. Neither of these machines is designed for hardcore gamers.

Since most of the Surface event focused on local AI agents, it’s not hard to tell who the Surface Laptop Ultra is designed for. So if you’re an AI developer who wants a laptop expressly built for that task, the Surface Laptop Ultra should suffice. However, we’ll need to do some hands-on testing to see if Microsoft’s laptop can handle local AI tasks better than a MacBook Pro — or the newly released Mac Studio M5 Ultra that’s also built for local AI.

More from Tom's Guide

• I spoke to Nvidia CEO Jensen Huang about RTX Spark
• I gamed for 250 hours on AMD Radeon RX 9070 GRE
• The MSI Claw 8 EX AI+ leaves ROG Xbox Ally in the dust

With Nvidia widely rumored to unleash RTX Spark alongside Microsoft on October 7, AMD decided it couldn’t wait. Team Red executed a preemptive strike to not just show off its shiny new (and expensive) Ryzen AI Max+ Pro 495 silicon, the company cheekily rebranded itself as “Agentic Micro Devices since 2025.”

Is this classic counter programming to plant a flag before Nvidia? Yes. But beneath the rush lies a piece of hardware with specifications so absurd they demand attention. Packing 16 desktop-class “Zen 5” cores and up to 192GB of unified memory, AMD’s built a brute-force x86 weapon designed to kill cloud AI subscription fees, take on Team Green and even make Apple a little nervous too.

The 192GB cheat code

To understand why AMD is sweating, look at what Nvidia is trying to pull off with RTX Spark. The team is aiming to make local AI agents accessible by pairing Arm-based compute cores with Blackwell graphics (a similar amount of cores that you find in the company’s desktop RTX 50-series GPUs) and unified system memory.

Apple, of course, wrote this playbook years ago with Apple Silicon in the MacBook Pro — proving that fusing a CPU and GPU around a giant pool of memory is the ultimate setup for intense tasks and heavy local models. And while Apple built the sandbox that Nvidia’s trying to take over, AMD just decided to dump a truckload of concrete into it.

If you want to run massive AI models locally on traditional laptops, the amount of memory means you simply cannot. Team Red’s Ryzen AI Max+ breaks that bottleneck through sheer volume to its digital brain:

• A 192GB shared reservoir: The CPU and GPU can share an enormous 192GB of memory running at a blistering 8.5 billion data transfers per second.
• The 160GB slider: I played with this on the Asus ProArt GoPro Edition with the AI Max+ 395. Using a feature called Variable Graphics Memory (VGM), users can carve out up to 160GB of that memory directly for graphics processing.
• The scale: This gives a single laptop more usable video memory (VRAM) than four desktop RTX 4090 cards strapped together. Not only is this huge for gaming (trust me, I tested it), but it allows for gargantuan 100+ billion-paramenter AI models to run entirely on-device and offline.

And that offline bit is critical in my mind. While I’m always going to take a look at the sheer amount of memory being gobbled up and think “oh, so that’s why RAMageddon’s a thing,” I am a believer that local AI is the future over cloud models like ChatGPT or Gemini.

Now, there are real-world examples to prove that.

Firing the cloud provider

Tech enthusiasts are tired of hearing “AI” attached to every bit of basic spreadsheet math, so AMD’s brought in Emmy-winning production studio LightSail VR to show off the economic reality of local agents.

This is the VR studio that recently caught a Sabrina Carpenter concert, and they deal with ultra-heavy 16K, 90 FPS stereoscopic 3D video for Hollywood. With client feedback pouring in across multiple projects, it was becoming overwhelming for the small team.

Option one of using cloud models like OpenAI or Anthropic to coordinate this is impossible for two reasons:

• Strict Hollywood NDAs: Confidential scripts, clips or project schedules cannot leave the four walls of their studio.
• The cloud meter: Running autonomous agents that constantly re-index documents and shift production timelines would burn thousands of dollars a month in cloud AI token costs.

So instead, LightSail VR build an in-house “production coordinator” agent on an AMD Ryzen AI Max desktop with unified memory — living directly inside the team’s personal Slack. It’s able to update schedules, rewrite spreadsheets and alert the team autonomously when an edit timeline shifts.

And the payoff has been huge, with the studio able to manage six to nine concurrent productions with the personal effort required for just two, with zero data leaving the building and zero cloud AI token invoices.

What does that mean for me?

But of course, you’re (probably) not producing 16K stereoscopic video for a Hollywood studio. Why should you care about a 192GB laptop processor? Simply put, the tech industry is currently trying to trap you in an endless web of AI subscription fees.

Right now, using a generative AI agent to organize your life or draft your emails comes with a hefty monthly premium fee. By building a laptop chip with massive unified memory, AMD is effectively stuffing that cloud server into a backpack.

That translates into two massive consumer victories:

• The death of the subscription tax: Buy the hardware once. After that, your autonomous digital intern can reorganize that messy hard drive, draft emails and analyze massive spreadsheets 24/7 without costing you a single cent in cloud AI costs.
• Absolute privacy: You no longer have to upload your tax returns, confidential work documents or personal schedules to a server in California just to get AI assistance. These gargantuan models can fit directly into the AI Max’s memory pool, so they run completely locally and offline.

It’s not just about raw horsepower; it’s a hardware escape hatch from the looming cloud subscription era.

The x86 moat against Arm

And that brings us to the core battlefield between AMD and Nvidia (and Apple to an extent).

RTX Spark leans into Arm architecture. Arm chips deliver exceptional power efficiency — as Apple has proved for years — but running traditional Windows applications on Arm requires translation layers.

And while Microsoft’s Prism emulation has improved massively (like Microsoft's engineer told me), translation layers still introduce power inefficiencies, occasional driver quirks and incompatibilities with legacy hardware.

In my experience with AMD, the team spent a significant chunk of its time exploiting that vulnerability and repeatedly mentioning “Native x86” alongside there being “no emulation layer” for Windows and Linux.

By sticking to the standard PC architecture of the past three decades, AMD avoids that trap entirely. Specialized software can run natively at full clip, older peripherals work out of the box, and when the work finishes, the integrated RDNA 3.5 graphics engine can natively fire up PC games without any chance of an emulator hiccuping mid-frame.

AMD’s scramble to share all of this two days before Nvidia takes the stage with Microsoft shows just how intense the pressure has become. Team Red is anxious that RTX Spark will set the narrative for what high-end AI laptops are supposed to look like.

But by using native x86 architecture and an audacious amount of money, AMD has ensured that when Nvidia steps into the spotlight, it won’t be walking into an empty room.

More from Tom's Guide

• I tested the Asus ROG Zephyrus G14 (2026) like I was a student — its gaming, creator and AI performance is huge, but it comes at a cost
• I just tested Windows 11 26H2 — here’s how to update now and why Microsoft finally fixed the two worst things about Windows 11
• I tested Microsoft’s fanless Snapdragon X2 Plus Surface Pro and Laptop: The MacBook Air should be terrified

It almost feels like blasphemy to play Gears of War: E-Day on PC — and to top it off, on Steam — rather than its natural home on Xbox. Almost. But after cranking up settings to Ultra, bumping up frame rates with Nvidia's DLSS 4.5 trickery and basking in ray-traced lighting, it was easy to take Marcus Fenix and his merry band of absolutely ripped soldiers beyond its console roots.

Developers The Coalition and People Can Fly are bringing the iconic third-person shooter back to the beginning: Emergence Day. That's when the gruesome Locust Horde army first emerged from the ground to cause chaos for the humans above, and that perfectly sets the stage for beautifully rendered mayhem and destruction.

After flanking and sawing my way through Locust (scum) for over 12 hours, I can say Gears of War: E-Day is the best the franchise has ever looked, and it's excellently optimized for PC gaming. From its highly detailed gore and destruction to its accurate lighting and shadows with RTX Mega Geometry, it nails the visual horrors of war and the smooth performance of its brutal, cover-based combat.

Even better, there's a huge variety of graphics settings to tinker with to get the right performance for your PC setup. It even includes a "Ludicrous" preset for power-hungry gaming rigs! So, is Gears of War: E-Day worth playing on PC? Yes, and for the reasons why, I've got you covered below.

Gears of War: E-Day PC Requirements

Gears of War: E-Day can be a demanding title to run, but it can also be as performance-driven and as light on your system as you need it to be, thanks to the lengthy list of graphics options and upscaling methods you can adjust.

While the developers are sure to have E-Day optimized for Xbox Series X/S, they've made sure to give the PC port some extra care so it can run on a majority of systems. That includes the best PC handhelds like the ROG Xbox Ally X.

While you won't need the best graphics cards to run the latest Gears of War installment, know that you will need a "hardware ray tracing-capable GPU," as the developers note. You'll also need a lot of space, so make sure you have enough storage.

Here are the official requirements, along with the PC specs I used.

Geared up for PC

Now, being made in Unreal Engine 5 (as many games have been recently) can be hit or miss, depending on the title. E-Day has been specifically rebuilt in Unreal Engine 5, but don't fret; it's a hit.

By taking Gears back to the devastating events of Emergence Day, the game has a lot of carnage to take advantage of. From massive locusts erupting from roads to the warm lights of a city at night disrupted by raging fires on exploded cars, E-Day knows how to showcase the atrocities of a sudden invasion by an unknown threat, and it's visually stunning.

That was all shown off in striking detail on a gaming PC that isn't exactly a beast of a rig, either. I played Gears of War: E-Day on the Quoted Tech Frontier gaming PC, with an AMD Ryzen 7 9700X CPU, Nvidia GeForce RTX 5070 GPU and 32GB of RAM. I was able to play in 4K and get a respectable 50 FPS on High settings, and I was still bursting Locust heads with smooth gameplay despite it being taxing on my system (there was a warning sign to say 4K would be a little much).

But that was without the boost from Nvidia's DLSS 4.5 Dynamic Frame Generation or Dynamic Upscaling Quality. With these toggled on, and even bumping up ray-traced shadows, reflections and geometry to Ultra, I was seeing Marcus, Dom and the rest of the team charging their way through hordes in crisp detail at a smoother 115 FPS. That's a green flag for PC optimization.

Now, this was the case in the more linear sections of the game. During a semi-open area I encountered, I noticed a few minor sudden dips in frames, cutting down by 15 to 20 FPS. That, and some pop-in artifacts every now and again. A deal-breaker? Not in the slightest, and something I could remedy myself.

Scaling back to 1440p resolution and switching to Performance upscaling gave me far smoother gameplay, and with frame generation at 6x? I was going well past 200 FPS, and my aging gaming monitor doesn't even go that high.

Being able to tinker with an assortment of settings to get the right balance of image quality and performance is always welcome, and Gears of War: E-Day has it in spades.

Lighting is on point

From the soft hum of street lamps lighting up a crumbling street in ruins to the tight, horror-like spaces in buildings being lit up with the glow from neon signs and TVs, E-Day shows that Gears of War has come very far from the gritty, desaturated browns that plagued late-2000s games. And it's only elevated further on PC with Nvidia's latest tools.

E-Day marks the first title to ray trace Nanite geometry, thanks to the added RTX Mega Geometry. Essentially, this means more realistic details in ray tracing, solving issues like missing or incorrect shadows, improved reflection quality, better stability for moving silhouettes and overall more geometry on objects to play with.

This isn't immediately noticeable, of course. Not when there's a mass of Locusts emerging from collapsing holes, charging at you with shotguns! But during the quieter moments exploring abandoned grocery stores, ravaged police stations and more, it's the ray-traced lighting and relfections that captures the atmosphere.

Switching RTX Mega Geometry on, the smaller details like the florescent lighting in the frozen section of a store bouncing off the floor, or the clear reflections of debris lying around on a blood-smeared window, are striking to look at. And having this on didn't appear to affect the performance of my gameplay, either.

This is subtle realism to make the surroundings of Marcus and his team feel more lived-in, which makes the war-torn city of Kalona far more engaging.

Optimized for destruction

As anyone playing games on the Xbox app, Steam or other clients will tell you, PC optimization is an important aspect of bringing any title to PC. Fortunately, we've seen many standout hits this year alone, and now this iconic Xbox franchise joins those ranks. Gears of War: E-Day is one of the best-looking PC games I've played in 2026, and that says a lot considering we've seen the likes of Control Resonant, Pragmata and Resident Evil Requiem arrive and impress.

While targeting 4K at 60 FPS on Xbox is already enough to show all the glorious, gory visuals E-Day has in store, playing the origins of the Gears of War saga on PC allows it to take advantage of the latest in graphics. I mean, cranking up the destructive details with 100+ FPS, along with scene-defining lighting and crisp reflections, is a treat for the eyes.

If this is the way AAA games are being treated on PC, I have high hopes for everything else to come (especially for the upcoming GTA VI).

For a closer look at our thoughts, be sure to check out our full Gears of War: E-Day review.

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• I gave the Steam Machine 3 stars at launch — but a game-changing update and this 1TB storage hack has me thinking differently
• I played Control Resonant on PC with Nvidia's DLSS Ray Reconstruction — and it beats PS5 Pro hands down
• I wanted to hate Nvidia’s DLSS 5 ‘AI filter’ — but the real DLSS 5 is photorealistic black magic

I’ve reviewed Zephyrus G14s for the past three years and the story is the same every year — one of the best ultraportable gaming laptops that money can buy (yes, even in this RAM price crisis). And I’ve tested them like the true millennial I am with my workload by day (plenty of Chrome tabs along with some creator work) and gaming by night.

So for this year’s model, I switched things up a bit. Of course I ran my usual gamut of benchmarks to establish how this fares as a gaming laptop (spoiler alert: it performs great). But let’s kick things up a notch with some more serious 3D rendering and local AI pipelines.

Like, say you’re a STEM student, 3D artist or video producer. What happens then? Well, the first thing you notice is just how those Tensor cores in the Nvidia GPU paired with that Intel Panther Lake CPU blaze through any AI task you throw at it — running my Hermes Agent locally was mightily impressive. Blender is a breeze on here and Premiere Pro is mightily powerful with a graphics card in tow.

And of course, all of this looks mesmerizing on that vibrant 2800 x 1800 120Hz OLED display. But getting more intense with it does start to show how hard those fans have to work in that slim shell. Plus, let’s not forget that the pricing has gone up quite a bit here — the RTX 5080 monster I tested last year was $100 less than this 5070 Ti option.

But then you see how the technically lower-end model performs better than the 5080 machine, you start to see how that redesigned ventilation is actually squeezing so much more sustained performance out of it. This is a peak improvement for the 2026 model, and while the fans do get loud, there is zero throttling. Asus solved a big issue here, and while that price stings, it does make this a great laptop.

Asus ROG Zephyrus G14 (2026): Cheat Sheet

• What is it? This is a premium 14-inch gaming laptop that doubles as a powerhouse for creative workflows and AI tasks.
• Who is it for? Serious gaming enthusiasts on the go, STEM students, 3D artist or video producers who need serious rendering muscle during the day.
• What does it cost? Pricing on Asus’ website starts from $3,599, but there is a model on Best Buy for $500 less.
• What do we like? The vibrant 2880 x 1800 120Hz OLED display is stunning, the overall performance is blistering (Handbrake transcoding in 3:19), and it packs massive local AI acceleration.
• What don’t we like? The 8-hour and 32-minute web battery life falls just short of a full workday, the fans get aggressively loud under load, and the high price puts it out of reach for casual users.

Asus ROG Zephyrus G14 (2026): Specs

Asus ROG Zephyrus G14 (2026): The ups

I’ll judge this on gaming for sure, but let’s lean a little bit more on the fact this can be a one-size-fits-all machine for local AI and creative pros alike, as well as a AAA play system. In that lens, this is huge.

The handy design tweaks

So yes, this is exactly the same physical design as last year’s model, and while that aesthetic may be getting a little old in its third year, it’s still a premium-looking and feeling machine with that CNC-machined aluminum body.

Keyboard ergonomics continue to feel great with a massive touchpad down below. All in all, having your hands on the G14 is still a nice place to be. But I don’t want to talk about that.

What I do want to talk about is the small but significant changes Asus has made that you may not see, but do come in clutch. First of all, sayonara microSD card — we’ve got a full-size SDXC card reader here. That’s been huge for my snap happy self porting footage over!

And second, that bottom panel has been redesigned to take air in much more efficiently. That means superior airflow access across all the internals and consistent sustained performance without any remote chance of thermal throttling.

Thanks to these new airflow paths and ventilation patterns, the total power going to the GPU has gone up from 110 watts all the way up to 130 watts. What you’re about to see in my numbers is how power matters a whole lot more than the card you have inside.

Serious silicon muscle

If you are a student or pro — compiling code or rendering video, this machine will not keep you waiting. That Intel Core Ultra 9 386H inside is posting lightning fast numbers on Geekbench, alongside transcoding 4K video rather fast.

Of course, Apple Silicon stays ahead in some key areas with a 4,000+ single-core speed, but that’s not the point of this laptop. This is your productivity machine by day and gaming monster by night, and with 6,144 MB/s read speeds on that SSD, large amounts of data load fast and those single-core speeds ensure zippy opens.

I never felt any stuttering or slowdowns in any process I threw at it.

Local AI and uncompromised gaming

That RTX 5070 Ti isn’t just for pushing pixels (even though it does that really well); it’s a localized AI powerhouse — absolutely crushing our benchmarks, but also opening a door to local agentic task completion via Hermes Agent.

Setting up my own personal assistant to give me a daily rundown of my emails, delete unnecessary ones and send replies, while setting me up a tasklist for the day while I drink my coffee has become a huge way to relax before my start of the day.

Throw in GPU-accelerated 3D rendering and 4K edits too, and you’re onto a winning formula for getting serious stuff done. These margins between 5070 Ti and 5080 are much closer than they should be, and the sustained performance is much stronger on the 2026 model to boot.

Then there’s the gaming, which essentially leapfrogs the RTX 5080 G14 because of that power differential we talked about!

Make no mistake about it. This is an all-round beast of a system.

Asus ROG Zephyrus G14 (2026): The downs

Same as previous Zephyruses, it’s not all a walk in the park. The G14 falls victim to two recurring issues from the last model, as well as a RAMageddon sting.

You’ll need to pack the charger

While the raw horsepower is strong for the big tasks, sometimes you just need to make the most of that highly-portable 14-inch shell to take to class or a coffee shop.