
As AI agents like Muse and Dots gain popularity, the workload shifts from GPUs to CPUs, revitalizing market leaders AMD and Intel.
AI-generated summary
The AI market was previously dominated by GPUs for model training and inference. The emergence of long-running autonomous agents has created a new requirement for CPU-heavy workloads.
The personal AI agent boom is giving Advanced Micro Devices and Intel new life after the companies spent years watching Nvidia and its GPUs dominate the artificial intelligence market.
The central processing unit, or CPU, was once the primary workhorse of a computer server before Nvidia's graphics processing units took center stage with the launch of ChatGPT and the start of the generative AI era. Now CPUs are back, lifting the fortunes of market leaders AMD and Intel, whose chips specialize in powering long-running agents that can work for hours on their own.
Last week OpenAI released its AI agent Dots, following the lead of Meta, which debuted Muse in early September. Muse caught on so quickly that it topped the Apple App Store in less than two weeks. Well before that, AMD and Intel were already huge winners in the stock market this year due largely to surging demand for CPUs, but they've picked up steam in the past month, jumping 32% and 21%, respectively, as of Monday's close beating all of tech's megacaps.
The rally continued on Tuesday, with AMD jumping almost 4% to a fresh high of $654.82 in mid-day trading. AMD's growing strength in both CPUs and GPUs has pushed the company into the trillion-dollar market cap club.
"As more agents are created and developed, and more people start to use them for more tasks, it's going to start to shift the workload away from GPUs and onto CPUs," said Ryan Shrout, president of Signal65, which consults on AI hardware and costs.
Users learned about the power behind the new agents by asking them. Muse tells users that it runs on an AMD-powered computer, while Dots said it runs on a virtual computer powered by AMD's EPYC-branded CPU.
A Meta spokesperson told CNBC that the company designed its system to use whatever kind of CPU is available.
"We take a diverse approach to our hardware and are largely CPU-agnostic by design, which gives us the most flexibility in acquiring capacity," the Meta spokesperson said in a statement.
OpenAI similarly uses multiple CPU providers, meaning AMD isn't the only game in town.
Most servers at hyperscalers — Amazon, Google, Meta and Microsoft — use CPUs made by Intel or AMD. But nearly every major cloud provider is also developing custom chips of their own, typically based on Arm technology. Arm announced its own CPU for agents in March, with Meta as the debut customer, and its stock price has more than doubled since.
Earlier this year, Nvidia released Vera — a fully redesigned central processor — along with an entire rack filled only with the CPUs. The chip giant says it built the new Vera CPUs specifically for agents and expects CPUs to be a $200 billion market by 2030.
But it's one part of the chip industry where Nvidia isn't currently the favorite, analysts say.
"It's just a new product and they're going to be competing against a lot of different players," Jordan Klein, an analyst at Mizuho Securities, said in an interview, adding that he believes AMD currently has the "best product."
CPUs are driving a healthy portion of AMD's growth. Revenue in the company's data center business more than doubled to $6.7 billion in the quarter ended in June, accounting for almost 60% of total sales.
"The conversation has changed quite a bit over the last eight to 10 months in terms of agentic usage," said Dan McNamara, AMD's senior vice president and general manager of compute and enterprise AI. McNamara added that CPU sales are going to "really ramp."
Muse, Dots and even coding software like OpenAI's Codex use AI models to plan tasks that can run autonomously. The agents need their own computer that can run for hours or even days in the background, explained Futurum Group CEO Daniel Newman.
GPUs are still needed for inference, or processing an AI model, but an agent also needs a CPU.
"CPUs are actually performing the workflows while GPUs are doing the thinking," Newman said.
Meta and OpenAI use virtual machines, which partition a server into several lighter virtual computers, so one server can support scores of users.
Some AMD EPYC processors have up to 192 CPU cores. According to benchmarks and the agents themselves, Muse's virtual computer uses two cores and Dots uses nine.
CPUs are less expensive than GPUs.
Benchmarks and queries show Dots using an AMD EPYC 9V74 CPU, which is available from resellers for under $3,000. The EPYC 9D25 reportedly used by Meta for Muse costs even less on the secondary market. Nvidia GPUs can cost more than 10 times that for a single chip, and they're usually sold in clusters of hundreds or thousands of chips.
Investors are watching how Meta plans to serve Muse users, after downloads surpassed 5 million since last month's launch, according to Sensor Tower. Morgan Stanley estimates Muse's serving costs at $3 to $130 per month, with an average of $37 per user, depending on inference usage.
The firm says Meta's agent could account for 20% of AMD's 2026 chip sales.
There's a lot of money to be made in CPUs, and forecasts for the segment's growth are accelerating.
Futurum estimates $118 billion in total CPU sales in 2027, almost double the firm's previous forecast in May.
In July, AMD predicted the entire CPU market would hit $220 billion in sales in 2030, up from a previous 2025 forecast of $60 billion. AMD said in July that it expects to take more than half of the market.
AMD currently commands about 46% of the market for x86 CPU units, Mercury Research said in August. Intel is also seeing a surge in demand.
But AMD has a foothold with hyperscalers, which is where many of the virtual machines for agents will be deployed. It also has the benefit of using an x86 architecture for its chips, allowing agents to use older software without worrying about compatibility issues.
"AMD is probably getting the most of this because they have the largest market share and the cloud hyperscaler world for CPUs," Klein said, adding that he "wouldn't rule Nvidia out."
"If you are a company that can supply both types of chips, you're in the best position," Klein said.
AI outlook — possibilities, not facts
CPU market to reach $200 billion by 2030.
Possible · Within years

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