The Acer Veriton GN100 is a monstrously powerful AI PC in a delightfully miniature package – a game-changer for AI deployment

Many conventional notebooks and ultraportables are being branded as AI PCs, despite their powers being limited by an integrated NPU that limits them to built-in Windows 11 features and OEM bloatware. The Nvidia DGX Spark is a different beast entirely. This specialized miniature workstation, powered by the GB10 Grace Blackwell Superchip, can tap into supercomputing-level performance.

Unlike conventional desktop PCs and mini PCs, this Linux-operated machine is a new class of machine designed for power users, AI developers, and software engineers, packing in a host of premium Nvidia components to deliver enterprise-grade performance to users who want to build and run their own models and workloads locally.

With Nvidia partnering with a host of OEMs for manufacturing and release, there are plenty of variants that you can choose from, including the excellent Asus Ascent GX10, Lenovo's ThinkStation PGX, and the Dell Pro Max with GB10, among others. These machines all adhere to the same dimensions and specs – but there will be slight differences in the build quality, overall design, thermal management, and pricing. Presently, we've got our hands on the Acer Veriton GN100 – a potent-looking machine that's priced at £3,999.99 in the UK.

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Acer Veriton GN100 review: Build and design

With clearly defined dimensions (150 x 150 x 51mm), OEMs will chiefly lean on the design of these machines to help their own stand out. Acer's design is incredibly sharp, with a set of vertical metallic grills cut with a horizontal bar, and beneath it, a protruding accent line running from left to right and dipping in the middle to give way for the logo.

The machine itself looks great on your desk and evokes an air of sophistication. For what it's worth, it's also one of the lightest DGX Spark iterations, weighing 1.2kg versus the Asus' 1.4kg. It's certainly a far cry from the machine this was based on – the 2016 DGX1, which cost $130,000 and weighed 61kg.

On the rear, you'll find the standard set of ports fitted into this class of mini workstation, arranged in a standard configuration beneath a stack of ventilation grills flush against the device's metallic surface. The ports include three USB-C 3.2 Gen 2x2 (20Gbps) ports with DisplayPort 2.1 compatibility, one USB-C Gen 2x2 with PD in, an HDMI 2.1 port, an Ethernet port, and a specialist Nvidia ConnectX-7 SmartNIC port that's used to link two of these mini workstations together for double the potency. You'll also benefit from wireless connectivity in the form of Wi-Fi 7 and Bluetooth 5.4 courtesy of a MediaTek card. We do lament the lack of additional ports like USB-A or an SD Card reader, but you can certainly connect peripherals to this machine with a dock or through a monitor.

Acer Veriton GN100 review: Specs and performance

Powering the Veriton GN100 is Nvidia's monstrous GB10 Superchip, which combines a 20-core Arm processor (10 Cortex-X925 performance cores and 10 Cortex-A725 efficiency cores) with a Blackwell GB20B GPU. This is a 5nm graphics card designed for specialized or low-power AI applications. Also included is 128GB LPDDR5x unified memory and a 4TB PCIe Gen5 NVMe SSD that offers the memory capabilities to support large language models and generative AI workloads. This is the same set of components you'll get in all Spark DGX machines, regardless of the OEM Nvidia has partnered with.

The machine is capable of reaching a petaFLOP of AI performance with FP4 precision (the 4-bit floating point numerical format for accelerated training and inference). This drops to 170 teraFLOPS with FP16 precision – the conventional standard for AI training and inference. Incidentally, these kinds of workloads typically require 37GB of memory bandwidth, which would more than blow out consumer-grade GPUs and render local AI practically impossible on standard machines. Indeed, this device presents a far higher ceiling for AI workloads than any conventional desktop PC or enterprise-grade workstation.

The machine also draws a maximum of 240W of power, but you're more likely to draw far less than that most of the time, unless you really push it to its upper performance limits.

Standard PC benchmarks are fairly irrelevant, offering a dim picture of what the machine is capable of. But, for what it's worth, testing via Geekbench 6 generated a staggeringly significant result of 3,106 for single-core performance and 19,192 for multi-core performance – roughly in line with the 3,104 and 20,048 we registered with the Asus Ascent GX10.

Anecdotal testing showed how you can run generative AI workloads, including image generation via ComfyUI and others, within minutes. Throughout usage, the machine barely made a sound and ran at a comfortable temperature – incredibly impressive for a device that's as capable and as compact as this is.

Acer Veriton GN100 review: Features

As you would expect with all variations of Nvidia's mini AI workstations, the Acer Veriton GN100 runs on the DGX OS platform, an Ubuntu 24.04 LTS (for ARM) Linux-based system. Compared with the vanilla version of Ubuntu, Nvidia has customized the overall look and feel to suit its unique design, color, and font scheme – and has packed the machine with plenty of out-of-the-box apps and services to get you started in running AI tasks.

From the desktop, you can easily seek out resources and links to Nvidia's library of AI 'playbooks', which are step-by-step guides that walk users through the purpose, setup, and best practices of running their own AI workloads. While a certain degree of technical knowledge is essential, these are fairly straightforward to follow – even if you've never used a Linux machine before – and make AI far more friendly and accessible to workers who may have never interfaced with custom-built generative AI before.

Ultimately, however, a machine like this is designed for power users who are keen to experiment with AI trials and deployments within their organizations, run local generative AI-based tasks without external connections, and create AI agents (and so many other uses). There are plenty of applications, from image generation and media manipulation to running VS Code or even building multi-agent chatbots. The playbooks are essential to the democratization of AI within the workplace, and really do help bring all workers up to speed.

The new Nvidia Sync feature also helps you connect your local desktop or laptop with the DGX Spark so you can operate these machines remotely within the same subnet – or via an IP address. You can launch applications remotely and share the display, while also accessing monitoring tools and other applications.

Acer Veriton GN100 review: Is it worth it?

This new class of AI-powered mini workstations is a game-changer for AI deployment within the workplace. In that spirit, the Nvidia-powered Acer Veriton GN100 is an exemplary machine that shows just how quick and easy it is to get started on running and experimenting with AI workloads.

We should note that this is not a machine for the conventional user, with Nvidia stressing that there's really no point in picking one up unless you plan on tapping into enterprise-grade performance levels courtesy of the GB10 Superchip. In many ways, this mini workstation will feel inaccessible or frustrating to those who predominantly work with conventional applications in Windows environments or have no need to develop and deploy AI tools.

For approximately £4,000, it's slightly cheaper than speccing out larger desktops like the Dell Pro Max Tower T2. That said, heads may be turned with the AMD Ryzen AI Max+ 395-based systems (codename Strix Halo), which run Windows 11 (a plus point for non-power users keen to learn how to use AI) and are available for a little less. However, the Acer Veriton GN100 is still a great system that serves as a fantastic entry point into the world of localized AI deployment.

Acer Veriton GN100 specifications