The “Magnificent Seven” — Nvidia (NVDA +3.87%), Alphabet (GOOGL 1.01%) (GOOG 1.06%), Apple, Microsoft, Amazon (AMZN 2.34%), Tesla, and Meta Platforms — collectively make up roughly 35% of the S&P 500 (^GSPC 0.06%). These companies can certainly move markets with their quarterly earnings reports. But as investors saw from the most valuable member of the group, Nvidia, Wall Street’s response to earnings can be relatively calm.
Nvidia delivered better-than-expected top- and bottom-line growth, announced a new $80 billion stock repurchase program, and a 2,400% increase in the quarterly dividend, and yet the stock barely budged — down less than 2% the day after the report.
Broadcom (AVGO +1.91%), which isn’t technically in the Magnificent Seven despite being worth more than Tesla and Meta, will report its second-quarter fiscal 2026 earnings on June 3. Here’s why its report matters more than any of the other Magnificent Seven companies.
Image source: Getty Images.
Broadcom is on the cutting edge of AI investment
A staggering 92% of Nvidia’s revenue from its most recent quarter came from data centers — driven by artificial intelligence (AI) demand for compute. Similarly, Broadcom is rapidly growing its AI semiconductor business, but it is also an AI networking powerhouse — guiding for 40% of total AI revenue in its upcoming quarter to come from networking — not chips.
While Nvidia is the leader in graphics processing units (GPUs), Broadcom specializes in designing AI accelerators, called XPUs. These chips are built for specific use cases, enabling cost savings and efficiency improvements at scale.
Broadcom partners with Alphabet to design Google’s Tensor Processing Units (TPUs). Google recently announced two new TPUs, the 8t for training and the 8i for inference. And on Broadcom’s March earnings call, CEO Hock Tan discussed in detail the need for separate custom chips for AI inference and training, and forecasted that XPUs will ultimately overtake the GPU design in data centers.
On Amazon and Alphabet’s latest earnings calls, both companies discussed their booming chip businesses, with Alphabet saying it may begin selling TPUs to select third parties and Amazon stating that if its chip business were a standalone entity, and it sold chips to third parties, it would have $50 billion in annual run rate revenue.
Custom AI chips are capturing the spotlight of hyperscaler spending budgets, and Broadcom stands center stage as the main act.
Outside of AI chips and networking, Broadcom has a sizable non-AI semiconductor business and an infrastructure software segment. Combined, these businesses made up more than half of its first-quarter fiscal 2026 revenue.
Today’s Change
(1.91%) $8.55
Current Price
$455.32
Key Data Points
Market Cap
$2.1T
Day’s Range
$442.36 – $460.38
52wk Range
$241.11 – $460.38
Volume
616K
Avg Vol
23.8M
Gross Margin
64.96%
Dividend Yield
0.56%
This earnings season’s main event
Broadcom’s earnings are arguably more important than any of the Magnificent Seven stocks because Broadcom is a barometer for the rapidly changing custom AI chip market for training and inference, the increasingly important AI networking industry, and the broader semiconductor and infrastructure software industries. While Alphabet and Amazon discuss their custom chips on earnings calls, Broadcom lays out the breadcrumbs of where hyperscaler spending is going and how modern-day mega-scale data centers are evolving.
What’s more, CEO Hock Tan and the Broadcom management team tend to go in-depth on the industry, with informative insights rather than just promotional talk. And so far, Broadcom has been spot on with some of its key predictions, including the massive push toward custom chips and larger networking clusters.
Broadcom’s runway for growth in AI chips and networking, combined with its legacy semiconductor and infrastructure software segments, makes it an excellent buy for long-term investors. But even investors who aren’t interested in directly investing in Broadcom should pay close attention to its June 3 earnings call, as it has ripple effects throughout the broader AI value chain.
