Suddenly, users no longer had to choose between performance and battery life. MacBooks became thinner, quieter and significantly more powerful, while a unified memory architecture allowed them to handle everything from video editing to AI workloads with remarkable efficiency.
Also Read: As AI shifts from training to inference, Intel moves up the stack
Six years later, Nvidia believes the next major shift in personal computing will not be driven by traditional applications at all, but by artificial intelligence (AI) agents.
At Computex 2026 in Taiwan, the company unveiled RTX Spark chip and with it, it is attempting something remarkably similar to what Apple did with Apple Silicon. Combine CPU, GPU and memory into a single system designed around a new era of computing. The difference is that while Apple built its chips around the Mac, Nvidia is building RTX Spark around AI.
What is Nvidia RTX Spark?
RTX Spark is Nvidia’s first serious attempt to move beyond discrete graphics cards and power entire personal computers.
ET OnlineThe chip combines a 20-core Arm-based CPU, a Blackwell GPU with 6,144 CUDA cores and up to 128GB of unified memory. Nvidia says the system can deliver up to one petaflop of AI performance and run AI models with as many as 120 billion parameters locally on a laptop.
The company has positioned RTX Spark as a chip built specifically for what CEO Jensen Huang calls the era of “personal AI agents” — software capable of performing tasks across applications with minimal human intervention. Nvidia is partnering with Microsoft to build Windows experiences around these agents, allowing users to run AI workloads directly on their devices rather than relying entirely on cloud services.
Major PC makers including Dell, HP, Lenovo, Asus, MSI and Microsoft Surface are expected to launch RTX Spark-powered devices later this year.
Why is everyone comparing RTX Spark to Apple Silicon?
The comparison is hard to ignore.
Like Apple’s M-series chips, RTX Spark combines Arm-based CPU cores, a powerful integrated GPU and large amounts of unified memory in a single package. The promise is similar as well: desktop-class performance inside relatively thin and portable devices.
For years, Apple Silicon has been the benchmark for efficient computing. Its combination of performance, battery life and unified memory helped Macs win over developers, creators and even AI enthusiasts looking to run large language models locally.
RTX Spark appears to be the closest thing Windows has seen to that vision so far. The chip is designed to deliver workstation-class AI performance without requiring the bulky laptops and power-hungry discrete GPUs traditionally associated with high-end Windows machines.
Where Nvidia may have an advantage
Ironically, Nvidia’s biggest advantage may not be the CPU at all.
The real attraction of RTX Spark is its Blackwell GPU and the CUDA software ecosystem that comes with it.
Unlike Apple, Nvidia already dominates AI development. Most modern AI models are trained and deployed on Nvidia hardware, and developers have spent years building software around CUDA, the company’s programming platform. RTX Spark effectively brings that ecosystem directly into laptops.
For AI developers, that could be a significant advantage.
The combination of a large GPU and up to 128GB of unified memory means RTX Spark systems may be able to run AI models locally that would otherwise require expensive cloud infrastructure or high-end desktop graphics cards. Nvidia is positioning the chip as a bridge between personal computers and data-centre AI infrastructure.
The company is also working closely with software makers including Adobe, Blackmagic Design and Blender. Adobe, for example, is rearchitecting Photoshop and Premiere Pro for RTX Spark, with Nvidia claiming up to twice the AI and graphics performance in some creative workflows.
Why Apple still has the upper hand in some areas
That does not mean RTX Spark automatically beats Apple’s latest M-series chips.
Several analysts note that Nvidia’s CPU cores are based on off-the-shelf Arm designs rather than the custom processors Apple develops in-house. Early assessments suggest Apple’s M5 chips are likely to retain advantages in CPU performance, power efficiency and battery life.
More importantly, Apple controls the entire computing stack.
Its chips, operating system and software are designed together, allowing for levels of optimisation that Windows hardware makers have historically struggled to match.
Nvidia, by contrast, must rely on Microsoft’s Windows-on-Arm ecosystem, which remains a work in progress. While compatibility has improved significantly, some applications and games still require emulation, which can affect performance. Analysts warn that Nvidia could face many of the same software compatibility hurdles that Qualcomm encountered with its Snapdragon-powered Windows PCs.
Also Read: Nvidia CEO Jensen Huang says robotics is South Korea’s next big sector, points to ‘some suprises’
The bigger story isn’t Apple. It’s AI.
The most important question may not be whether RTX Spark beats Apple’s M-series chips. Instead, it is whether Nvidia can create a new category of AI-first computers.
For decades, personal computers have largely been defined by applications. Users open a browser, launch software and manually complete tasks. Nvidia believes AI agents could change that model entirely, allowing users to describe what they want done while software handles the execution.
That vision remains largely unproven. But it helps explain why Nvidia is entering a market traditionally dominated by Intel, AMD and Apple.
As Patrick Moorhead, chief analyst at Moor Insights & Strategy, noted in a LinkedIn post, the company’s ultimate goal may be less about selling laptops and more about extending its CUDA ecosystem from notebooks all the way to data centres. In that sense, developer lock-in could prove more valuable than hardware sales themselves.
Verdict: Can RTX Spark do for Windows what Apple Silicon did for Macs?
The short answer is: not yet.
Apple Silicon succeeded because it combined breakthrough hardware with deep software integration and immediately improved the experience for millions of mainstream users.
RTX Spark appears to be targeting a narrower audience initially — AI developers, creators and power users willing to spend thousands of dollars for local AI capabilities. Analysts expect many systems to cost between $3,000 and $4,000, putting them in direct competition with high-end MacBooks.
But if Nvidia succeeds in making AI agents a core part of personal computing, RTX Spark could become something just as significant: the chip that turned Windows PCs into AI-native machines.