Advanced Micro Devices reported first-quarter results that topped analysts’ estimates.

For the second quarter, the chipmaker stated it expects about $11.2 billion in revenue, beating expectations.

AMD’s stock has more than tripled over the past year as investors bet that the artificial intelligence boom is just getting started.

Advanced Micro Devices reported first-quarter earnings Tuesday that topped expectations, while the company’s revenue forecast also exceeded estimates as demand soars for chips to power artificial intelligence workloads.

The stock jumped about 15% in extended trading. Furthermore, experts in bear market note the continued relevance.

Here’s how the chipmaker did versus LSEG consensus estimates for the quarter ended in March:

EPS: $1.37 vs. $1.29 adjusted expected

Revenue: $10.25 billion vs. $9.89 billion expected

Revenue climbed 38% from $7.44 billion a year ago, the organization mentioned in a release on Tuesday. Data center sales increased 57% to $5.8 billion from $3.67 billion in the same period a year earlier. Net income rose to $1.38 billion, or 84 cents per share in the quarter, from $709 million, or 44 cents per share, a year ago.

For the second quarter, AMD noted it expects about $11.2 billion in revenue, versus expectations of $10.52 billion, according to LSEG.

AMD CEO Lisa Su commented in the statement that the data center unit is now the “primary driver of our revenue and earnings growth.” This also touches on aspects of earnings report.

“Looking ahead, we expect server growth to accelerate meaningfully as we scale supply to meet demand,” Su remarked.

In prepared remarks ahead of the earnings call, Su noted the enterprise has “strong and increasing confidence” in its ability to reach tens of billions of dollars in data center AI revenue next year “and to exceed our long-term growth target of greater than 80 percent in the coming years.”

AMD’s stock has been on a tear, more than tripling over the past year, including a 66% jump so far in 2026. While the business has trailed far behind rival Nvidia in the marketplace for graphics processing units (GPUs) to power AI data centers, investors have poured into AMD’s stock more recently on optimism that the opportunity is large enough for multiple players.

Unlike Nvidia, AMD has long been a leading maker of central processing units, or CPUs, which are enjoying a major renaissance as agentic AI shifts compute needs. AMD shares popped last week when AMD and Intel proclaimed they’ll pair up on a updated instruction set for x86 CPUs. The novel feature, called AI Compute Extensions, aims to rise performance and energy efficiency by boosting compute density by 16 times.capacity constraints for both manufacturing and advanced packaging along with

The chip industry has faced a global memory shortage because of insatiable AI demand, and supply chain challenges due to the war in Iran.

That’s all contributing to a frenzy in a number of semiconductor-related names. Intel just had its best month ever in April, with shares more than doubling as the corporation reported first-quarter results that trounced analysts’ estimates. Shares of memory maker Micron are up more than 700% in the past year, pushing the company’s sector cap past $700 billion.

Besides CPUs and GPUs, AMD is also expected to ship its first full rack-scale system for AI data centers, Helios, later this year. It’s meant to rival Nvidia’s Grace Blackwell and Vera Rubin systems that auction for upwards of $3 million.

Both OpenAI and Meta have already signed up for shipments of Helios, marking AMD’s system as a viable second option for AI giants and hyperscalers scrambling to secure enough compute.

Meta stated in February that a multiyear deal with AMD involves deploying up to 6 gigawatts of the company’s GPUs for AI data centers and includes apply of AI-optimized CPUs.

Su remarked in her prepared remarks that shipments are set to begin in the second half of the year.

“Together with our previously proclaimed OpenAI partnership, these engagements position AMD as a core partner to the world’s largest AI infrastructure builders, with deep co-engineering relationships and multi-year visibility into large-scale deployments,” Su mentioned.

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