RTX Spark vs DGX Spark: What's the Difference?

Nvidia RTX Spark and Nvidia DGX Spark are not the same product wearing two badges — they are two different machines, running two different operating systems, built for two different buyers, that happen to share a confusing surname. If you're a consumer or gamer who wants a Windows PC that can run AI agents locally, RTX Spark (shipping to laptop buyers October 16, 2026) is the one to look at. If you're a developer, researcher, or startup that needs a Linux box to prototype, fine-tune, and test large AI models before deploying them to the cloud, DGX Spark (on sale now, with a new 64GB model arriving October 23) is the one you actually want. Below is what each machine is, what it costs, and how to tell them apart in under a minute.

What is RTX Spark?

RTX Spark is Nvidia's name for a new superchip platform built into Windows 11 laptops and small desktops, announced jointly with Microsoft as part of a push toward what the companies call "agentic AI PCs." Nvidia's own description, from the RTX Spark product page, frames it as bringing "AI development, creating, and gaming — all on one Windows PC."

Under the hood, the top configuration pairs a 6,144-core Blackwell RTX GPU with a 20-core Grace CPU (an Arm design using Cortex-X925 and Cortex-A725 cores), linked by Nvidia's NVLink-C2C interconnect at up to 600 GB/s, with up to 128GB of LPDDR5X unified memory shared between CPU and GPU. Nvidia rates the chip at roughly 1 petaflop of FP4 AI performance. A second, lower configuration trims that to a 5,120-core GPU, an 18-core CPU, and up to 64GB of memory, aimed at thinner laptops. Both configurations run CUDA natively on Windows 11 and include 4th-generation RT cores, 5th-generation Tensor cores, DLSS 5, and Reflex 2.

The pitch isn't just raw silicon — it's the software wrapped around it. Nvidia and Microsoft are introducing new Windows security primitives (covering agent identity, containment, and policy) alongside NVIDIA OpenShell, a runtime that lets a user define what an AI agent is allowed to do, decides when a task should run on the local chip versus the cloud, and can mask personal information before anything leaves the device. Early software partners building on OpenShell include Nous Research's Hermes Agent and OpenClaw, according to Nvidia's RTX AI Garage blog post on the platform. Nvidia says the hardware can keep models as large as 120 billion parameters, with context windows up to 1 million tokens, running entirely on the device rather than in a data center.

What is DGX Spark?

DGX Spark is a different machine entirely. It's a compact, Linux-based desktop that Nvidia markets as a "personal AI supercomputer" for developers, built around the GB10 Grace Blackwell Superchip — a 20-core Arm CPU (again Cortex-X925 and Cortex-A725) fused to a Blackwell GPU with 5th-generation Tensor Cores and 4th-generation RT cores. Nvidia's DGX Spark product page describes it plainly: it's "designed to build and run autonomous agents," aimed at developers, researchers, and data scientists who need to prototype and validate AI models locally before moving them to the cloud or a data center.

Specs-wise, DGX Spark also tops out around 1 petaflop of FP4 compute, with up to 128GB of coherent unified memory (a 64GB configuration exists too, sold only through OEM partners) across a 256-bit memory bus delivering 273 GB/s of bandwidth, according to Nvidia's own developer blog benchmarks. It packs up to 4TB of self-encrypting NVMe storage, a ConnectX-7 networking card capable of 200 Gbps, 10GbE, Wi-Fi 7, and the ability to link up to four units together to pool memory for larger models. Nvidia's own system overview documentation lists the unit at 150mm x 150mm x 50.5mm and 1.2kg, running on a 240W power supply with the GB10 chip itself rated at 140W TDP. It ships with DGX OS (Nvidia's Ubuntu-based Linux distribution), not Windows.

Why everyone is typing "RTX Spark vs DGX Spark" into Google

The confusion is understandable, and it's mostly Nvidia's fault. Both products are built around Blackwell-generation silicon fused to a 20-core Arm Grace CPU. Both claim roughly 1 petaflop of FP4 AI performance. Both top out at 128GB of unified memory. Both are explicitly pitched at running AI agents locally instead of in the cloud. And both carry the "Spark" name. From a headline spec sheet, they can look almost identical.

The actual differences are in the operating system, the software stack, the form factor, and — most importantly — the target buyer. DGX Spark runs Linux and ships with Nvidia's full CUDA/AI Enterprise developer stack, NGC container support, and tools meant for building and training models. RTX Spark runs Windows 11, is sold inside laptops and small desktops from mainstream PC brands, and is built for gaming, creative work, and consumer-facing AI agents alongside everyday computing. One is a workstation for people who write AI software; the other is a PC for people who use AI software (and also want to play games and edit video).

RTX Spark vs DGX Spark: specs and price side by side

Price and release dates: what's confirmed, what isn't

DGX Spark's pricing is the better-documented of the two, as Pandromeda covered in its DGX Spark 64GB release date and price breakdown: the 64GB configuration goes on sale October 23, 2026, from Acer, ASUS, Dell, Gigabyte, HP, and MSI, starting at $4,999. The original 128GB Founders Edition launched in 2025 at $3,999, but Nvidia's current product page does not list a direct retail price for that configuration — it instead routes buyers to a "Buy Now" marketplace link and authorized retailers such as Amazon, Micro Center, PNY, and TD SYNNEX, where prices have fluctuated with memory supply costs. Treat any 128GB figure you see outside Nvidia's own page as a retailer price, not an official Nvidia list price.

RTX Spark's pricing picture is less settled. Nvidia's RTX Spark product page lists no prices at all — only "Preorder Now" and "Email Me When Available" buttons across its OEM lineup (ASUS ProArt P16, Dell XPS 16, HP OmniBook Ultra 16, Lenovo Yoga Pro 9n, Microsoft Surface Laptop Ultra, and MSI Prestige N16 Flip AI+). The one confirmed number, as covered in Pandromeda's report on Nvidia and Microsoft's agentic AI PC launch, is Microsoft's own Surface Laptop Ultra, listed for preorder at $2,599.99 ahead of its October 16 ship date. Pricing for the other five OEM laptops, and for RTX Spark compact desktops (due in November 2026), had not been published by Nvidia as of this writing. Treat broader RTX Spark pricing as unconfirmed until individual OEMs publish their own numbers.

Who should actually buy RTX Spark

RTX Spark makes sense if you want one Windows machine that covers gaming, content creation, and everyday computing, and you'd also like it to run AI agents locally rather than farm every request out to the cloud. Nvidia's pitch leans on DLSS 5, Reflex 2, and ray tracing for games; 4:2:2 video and HEVC/H.264/AV1 support for creators; and OpenShell-managed agents for people who want an assistant that can act on personal data without necessarily sending it to a server. If you're buying a new laptop anyway and the agentic-AI angle is a bonus rather than the whole point, RTX Spark's OEM laptops — arriving from six major PC brands starting October 16 — are built for exactly that.

It's a worse fit if you need a serious model-training or fine-tuning workstation. RTX Spark runs Windows, not the Linux-first CUDA developer stack that DGX Spark ships with, and it's priced and marketed as a premium consumer PC, not a lab tool.

Who should actually buy DGX Spark

DGX Spark is built for people who write AI code for a living: developers fine-tuning models up to roughly 70 billion parameters, running inference on models up to roughly 200 billion parameters, or prototyping agentic workflows before moving them onto Nvidia's DGX Cloud or a data center cluster. It ships with DGX OS, Nvidia's AI software stack preinstalled, NGC container access, and — for teams that outgrow one box — the ability to link up to four units together to pool memory for bigger jobs. Robotics and computer-vision teams working with Nvidia's Isaac, Metropolis, or Holoscan platforms are also squarely in Nvidia's target audience for the device.

If your actual job is building and testing AI models rather than using a finished product, DGX Spark is the one built for that job, even though it costs more and offers none of the gaming or Windows-app compatibility that RTX Spark provides. Pandromeda's existing look at how DGX Spark compares against AMD's Ryzen AI Max 395 covers that developer-workstation decision in more depth if your real choice is between DGX Spark and a non-Nvidia alternative.

Can RTX Spark do a developer's job, or can DGX Spark game?

Partially, in both directions, but neither is really built for the other's job. RTX Spark does run CUDA natively, so simple local-model experimentation is technically possible on it, and Nvidia is explicitly marketing "AI development" as one of its three pillars alongside creating and gaming. But it lacks DGX OS, Nvidia's preinstalled AI Enterprise stack, the clustering option, and the Linux-first tooling most AI engineering teams build around. DGX Spark, on the other hand, runs DGX OS rather than Windows, has no listed gaming features, DLSS, or Reflex support, and is priced and positioned purely as a developer tool — it isn't going to replace a Windows gaming laptop. If your work genuinely spans both worlds, that's two separate purchases, not one machine doing double duty.

Frequently asked questions

Is DGX Spark being discontinued because of RTX Spark? No. Nvidia continues to sell and update DGX Spark — including the new 64GB configuration arriving October 23 — alongside the RTX Spark launch. They're parallel product lines, not a replacement.

Do RTX Spark and DGX Spark use the same chip? No, but they're close cousins. Both pair a Blackwell-generation GPU with a 20-core Arm Grace CPU and roughly 1 petaflop of FP4 compute, but RTX Spark's configurations (up to 6,144 CUDA cores) and DGX Spark's GB10 Superchip are distinct designs built for different operating systems.

Can I run Windows games on DGX Spark? Nvidia doesn't market or document DGX Spark for gaming. It runs DGX OS, a Linux distribution built for AI development, not Windows.

Why doesn't Nvidia list a price for RTX Spark yet? Pricing is set by each OEM partner. Only Microsoft's Surface Laptop Ultra has a confirmed preorder price so far; the other five launch laptops had not published pricing as of this writing.

Which one is cheaper? Based on confirmed numbers, DGX Spark's 64GB model at $4,999 and Microsoft's RTX Spark-powered Surface Laptop Ultra at $2,599.99 are the only two hard prices available, making the Surface the cheaper confirmed option — though most RTX Spark OEM pricing still hadn't been announced.

What to do next

Figure out which job you're actually trying to solve before you shop by name alone. If you want a Windows laptop or small desktop that games, edits video, and runs AI agents locally, watch for RTX Spark laptops shipping October 16, 2026, and wait for OEM pricing beyond the confirmed $2,599.99 Surface Laptop Ultra before committing. If you're a developer, researcher, or startup that needs to build, fine-tune, or test AI models on your own hardware, DGX Spark — especially the new $4,999 64GB model landing October 23 — is the Nvidia "Spark" actually built for that. The safest rule: if the box runs Windows and shows up in a laptop aisle, it's RTX Spark; if it runs Linux and is marketed to developers, it's DGX Spark.

Written byMara Lindqvist

Mara Lindqvist edits the hardware desk. She covers graphics cards, processors, memory and storage, the foundries and chip designers behind them, and what the numbers on a spec sheet mean for people choosing a PC. Specifications in her stories come from manufacturer spec pages and datasheets.

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