Nvidia Plans Long-Term Development of RTX Spark, Announces N2X and N3X Chips

Nvidia has no intention of stopping with its recently unveiled consumer laptop chip, the “RTX Spark.” At Computex 2026, currently taking place in Taiwan, the company’s CEO Jensen Huang announced plans for at least two next-generation chips, the “N2X” and “N3X.” Huang stated that the ultimate goal is to realize computers akin to those seen in science fiction, operated entirely by voice commands.

“I want to talk to my laptop. I want my own R2-D2,” Huang told analysts and investors. This vision stems from Nvidia’s collaboration with Microsoft CEO Satya Nadella, which began around three years ago, to build AI-native Windows PCs.

The Vision Shared at Computex

On stage at Computex, Huang painted a picture of a future where users can simply talk to their Windows PCs, saying something like, “Hey, do this.” He likened this vision to the iconic scene in the movie Star Trek IV, where the Enterprise’s engineer Scotty travels back in time and attempts to talk to a computer by speaking into a mouse, asking, “Computer?”

“In the future, this computer will be AI. Everything will be AI. Even vacuum cleaners. You’ll be able to say, ‘Mop that spot,’ and it will do it,” Huang continued.

However, Huang’s vision of an “R2-D2” doesn’t necessarily require the device to be physically present. Drawing inspiration from Star Wars, he proposed scenarios where users could send commands to their laptops remotely.

“Today, if you want to talk to your laptop, you have to wait until you go back to your room. In the future, you’ll just need to send a text through WhatsApp. For example: ‘R2-D2, on PowerPoint slide 17, the scale of that image or the title is wrong. Change CX9 to CX10.’ R2-D2 will open PowerPoint, make the edit, convert it into a PDF, and send it back to you. Can you imagine that? It’s simple.”

The Economics of Local AI Execution

If remote control is possible, why not just rely on cloud-based AI instead of purchasing expensive laptops? To this question, Huang cited economic reasons.

“We don’t want to run everything in the cloud. If we can run it locally, it’s free. Would you rent a TV? Something you use every day. Would you rent a washing machine? Perhaps once a week. Would you rent a refrigerator? Something you use every day. Would you rent an assistant computer? You’d use it daily.”

This perspective succinctly explains why Nvidia is focusing on the RTX Spark. Cloud-based AI incurs ongoing usage fees, whereas local execution requires a one-time investment with no recurring costs. Given that laptop replacement cycles span several years, Nvidia estimates that local AI execution will be more cost-effective in the long run.

Huang also suggested that owning your own machine offers unique advantages, such as enhanced data privacy, greater freedom for customization, and availability that does not rely on internet connectivity — benefits that are not achievable with cloud-based solutions.

The Role of N2X and N3X

The N2X and N3X chips, which Huang revealed, are positioned as successors to the recently announced RTX Spark. While specific specifications and release dates remain undisclosed, the revelation that at least two more generations are already being developed underscores Nvidia’s commitment to the consumer AI laptop market.

Nvidia has historically dominated the gaming-oriented GeForce series and data center AI accelerator markets. However, the consumer laptop CPU market is a highly competitive space, with established players like Intel, AMD, Apple, and Qualcomm vying for dominance. RTX Spark represents Nvidia’s ambitious entry as the “fifth player” in this space, aiming to gradually expand its market share with the N2X and N3X chips.

The collaboration with Microsoft, initiated three years ago, is particularly significant. Tight integration between an operating system provider and a chip manufacturer is essential for performance optimization and the implementation of new features. By working closely with Microsoft, Nvidia has secured a role that goes beyond hardware supply, allowing the company to influence the overall design of the platform experience.

Comparing the Competitive Landscape

In the current laptop CPU market, Apple has achieved high levels of AI performance and power efficiency with its in-house M-series chips, while Qualcomm’s Snapdragon X series features NPUs designed specifically for AI processing. Intel and AMD have also introduced their latest architectures with integrated AI accelerators, leading to a surge in laptops boasting advanced AI capabilities.

Amid such fierce competition, Nvidia’s strength lies in its decades of expertise in GPU parallel processing and its CUDA ecosystem. While the architectural details of RTX Spark have not been disclosed, Nvidia’s advanced AI inference optimization technologies could provide a clear competitive edge.

However, there are significant challenges to developing processors for laptops, including issues surrounding x86 and ARM licensing, achieving a balance between power efficiency and performance, and ensuring compatibility with existing software. How Nvidia overcomes these hurdles will be key to the success of the N2X and N3X.

Editorial Opinion

Short-Term Impact: The announcement at Computex and the confirmation of plans for two more generations of chips signal Nvidia’s strong commitment to the consumer AI laptop market. Once RTX Spark-equipped PCs begin to hit the market in late 2026 or early 2027, competitors will likely feel the pressure to enhance their AI capabilities. Nvidia’s closer relationship with Microsoft could also have a ripple effect on the development of a robust Windows on ARM ecosystem. However, the market’s reaction will ultimately depend on the actual performance and power efficiency of the first generation of RTX Spark chips.

Long-Term Perspective: Huang’s “Star Trek computer” vision represents more than just a product roadmap; it reflects an ambition to fundamentally transform how computing is done. As voice-driven natural language interactions become more mainstream, the current GUI-centric user experience could undergo a dramatic shift. Particularly, the use case Huang described — sending a text via WhatsApp to remotely command a laptop — hints at a new paradigm for remote work. Over the next one to three years, PCs with AI agents integrated at the OS level could become the norm, with users transitioning from “opening an app” to “delegating tasks.”

Editorial Questions: While Nvidia’s long-term plans are compelling, questions remain about whether local AI execution can truly be considered “free.” While there are no recurring costs, the high upfront price of a laptop with advanced AI chips could be a significant barrier. Additionally, as cloud-based AI continues to evolve, there is a risk of local models becoming obsolete. While Huang’s analogy about not renting washing machines or refrigerators is intuitive, how much would readers be willing to pay for an AI-powered laptop? Moreover, as voice-operated technology becomes more common, new privacy and security challenges are likely to emerge. These are important topics for further discussion.

References

• Nvidia is already planning N2X and N3X chips — the goal is the Star Trek computer - The Verge — Published on 2026-06-03
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