> ## Content Index > Fetch the complete content index at: https://beirutwire.com/llms.txt > Use this file to discover other available public pages before exploring further. # Nvidia Expands Into the CPU Market, Challenging Intel and AMD’s Longtime Dominance - URL: https://beirutwire.com/nvidia-expands-into-the-cpu-market-challenging-intel-and-amds-longtime-dominance/ - Published: 2026-10-20T06:36:33.000Z - Updated: 2026-10-20T06:36:33.000Z - Description: Nvidia is expanding into the traditional CPU market with its Vera processor, winning AI cloud startup Modal as a customer after early tests showed significant performance improvements over Intel and AMD chips. - Author: Beirut Wire - Tags: Business Nvidia is expanding beyond the graphics processors that made it the dominant force in artificial intelligence, targeting another enormous segment of the semiconductor industry: central processing units. The company has secured a major new customer for its Vera CPU, with fast-growing AI cloud startup Modal announcing that it will incorporate Nvidia's processors into its computing infrastructure. Until now, Modal had relied on processors from Intel and AMD. That is beginning to change. According to Reuters, early testing showed that Nvidia's Vera chips completed certain AI-agent tasks roughly twice as fast as existing Intel and AMD alternatives, prompting Modal to begin integrating them into its systems. The development marks an important step in Nvidia's effort to challenge the companies that have dominated the CPU market for decades. And it is happening because artificial intelligence is changing what computers need to do. For most of its history, Nvidia was best known for graphics processing units, or GPUs. These chips were originally designed to render graphics for video games. Their ability to perform enormous numbers of calculations simultaneously eventually made them ideally suited for training and running artificial intelligence models. That transformed Nvidia into one of the world's most valuable companies. Today, its processors power much of the global AI industry, including infrastructure used by OpenAI, Anthropic and major cloud providers. But GPUs are only part of a computer. Every system also needs a central processing unit. Traditionally, Intel and AMD have dominated this market, supplying the processors responsible for running operating systems, executing instructions, managing applications and coordinating computing tasks. GPUs handle massive amounts of parallel computation. CPUs manage the broader computing environment. Nvidia now wants to control both. Its latest processor, Vera, is specifically designed for the emerging world of AI agents. That distinction is important. A traditional AI chatbot receives a prompt, generates an answer and stops. An AI agent can perform complex sequences of work. It can search the internet, write computer code, execute programs, access databases, operate software, analyze documents and repeatedly evaluate its own results. Those activities require substantial CPU processing power. As AI systems become more autonomous, the demand for CPUs capable of supporting them is increasing rapidly. Nvidia believes this creates an opportunity to enter a market that was historically dominated by Intel's Xeon and AMD's EPYC processors. The company estimates the addressable market for its new CPU products at approximately $200 billion. It is targeting at least $20 billion in revenue from Vera processors during its current fiscal year, according to Reuters. That would represent a major new business even by Nvidia's standards. The company has already made significant progress. Its earlier Grace CPU, introduced in 2021, generated more than $5 billion in revenue over the preceding 12 months, according to Nvidia's August earnings disclosures. Vera builds on that foundation. The processor uses 88 custom Arm-compatible CPU cores and a high-bandwidth memory architecture designed to manage the demanding workloads associated with AI agents. Nvidia says the chip can complete certain tasks approximately 1.8 times faster than conventional x86 processors while delivering substantially greater memory bandwidth per watt. These figures are based on specific workloads and benchmarks, rather than evidence that Vera is universally faster at every computing task. But early customers are beginning to validate the company's strategy. Modal is particularly interesting because its entire business is built around providing computing infrastructure to AI developers. The startup has experienced extraordinary growth as companies increasingly deploy AI agents that operate continuously rather than simply respond to occasional prompts. Modal recently raised $750 million at a valuation of approximately $15.75 billion. Its revenue has reportedly increased fifteenfold over the past year, while usage of its services has tripled. The company expects annual sales to reach approximately $1 billion in the coming year. That makes its hardware decisions particularly relevant. Modal's infrastructure must handle large numbers of software environments, programming tasks and automated workflows. These are precisely the workloads Nvidia designed Vera to accelerate. However, Modal is not abandoning Intel or AMD entirely. Its CEO, Erik Bernhardsson, said the company intends to maintain a mixed hardware strategy, choosing processors according to workload requirements and performance. That highlights an important limitation to Nvidia's expansion. Intel and AMD still possess enormous advantages. Their x86 processors support decades of software development, enterprise infrastructure and technical expertise. Many companies depend on systems optimized specifically for that architecture. Replacing them is not as simple as demonstrating faster performance in one benchmark. Nvidia's Vera processors use an Arm-compatible architecture, meaning software compatibility and migration requirements will remain important considerations. Still, the broader direction is significant. Nvidia has already attracted interest from major technology companies, including OpenAI, Anthropic and Oracle. Perplexity previously announced plans to adopt Vera after observing improvements in AI-agent coding workloads. Major server manufacturers, including Dell, Hewlett Packard Enterprise, Lenovo and Supermicro, are also developing systems around the processor. Nvidia is therefore not simply releasing another chip. It is building an entire computing ecosystem. That is the larger business strategy. For years, Intel and AMD supplied CPUs while Nvidia supplied GPUs. Data-center operators combined products from different manufacturers to build complete systems. Now Nvidia wants to provide an increasing share of that infrastructure itself. It already sells AI accelerators, networking equipment, software platforms and integrated computing systems. Adding competitive standalone CPUs allows it to capture more revenue from each data center. It also potentially gives Nvidia greater control over how AI workloads are designed and optimized. That matters because the artificial intelligence industry is moving toward increasingly integrated hardware. The winners may not simply be the companies producing the fastest individual chips. They may be those capable of delivering complete systems that reduce electricity consumption, improve performance and lower the cost of running AI models. Nvidia's expansion also arrives at an awkward moment for Intel. The company has spent years trying to restore its technological competitiveness while facing pressure from AMD and Arm-based processors. AMD has meanwhile increased its share of the server market through its EPYC product line. Both companies now face another competitor with enormous financial resources, close relationships with leading AI developers and a powerful position in data-center infrastructure. Nvidia's entry does not mean Intel and AMD are about to disappear. Nor does it mean Nvidia is immediately taking over the traditional laptop and desktop processor market. Its strongest initial opportunity is in servers designed for AI workloads. But that market is becoming increasingly important. As AI agents spread through businesses, demand for computing will no longer be driven exclusively by training large models. It will also come from millions of automated systems continuously performing work. Those systems need GPUs. They also need CPUs. Nvidia wants to sell both. The company already became the dominant supplier of the chips that helped create the AI revolution. Now it is positioning itself to power the computers that will run the next stage. For Intel and AMD, that means the AI boom is no longer simply an opportunity to sell more processors. It is also bringing one of the world's most formidable semiconductor competitors directly into their territory.