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Broadcom Q3 2026 Earnings Analysis

Sep 3, 2026 · 7m 27s
Broadcom Q3 2026 Earnings Analysis
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More earnings analysis: https://betafinch.com Groups: CHIPS (https://betafinch.com/groups/CHIPS), AI_LEADERS (https://betafinch.com/groups/AI_LEADERS) ────────── WELCOME TO BETA FINCH, your AI-powered earnings breakdown. I'm Alex, joined as always by Jordan, and today we're digging into...

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More earnings analysis: https://betafinch.com
Groups: CHIPS (https://betafinch.com/groups/CHIPS), AI_LEADERS (https://betafinch.com/groups/AI_LEADERS)
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WELCOME TO BETA FINCH, your AI-powered earnings breakdown. I'm Alex, joined as always by Jordan, and today we're digging into Broadcom's fiscal Q3 2026 numbers—and folks, these are some genuinely wild numbers.

ALEX: Before we get into it, quick reminder: this podcast is AI-generated content for educational and entertainment purposes only. Nothing we discuss should be considered investment advice. Always do your own research and consult a qualified financial advisor before making any investment decisions.

JORDAN: And it's a good quarter to have that disclaimer front and center, because Hock Tan basically stood up and said "we're just getting started," and then backed it up with a $230 billion revenue forecast for 2028.

ALEX: Let's start with the headline numbers. Q3 revenue came in at $29.6 billion, up 86% year-on-year. Operating income hit $20.1 billion, up 92%, with a record 68% operating margin. And free cash flow? $13.7 billion, 46% of revenue.

JORDAN: Those margins are the story for me. Gross margin actually dipped slightly, down to about 75%, because AI chips carry more memory content and lower margins than the rest of the business. But operating margin still climbed because revenue is growing so much faster than expenses. That's operating leverage doing exactly what it's supposed to do.

ALEX: Right, and the AI piece specifically—AI semiconductor revenue was $16.7 billion for the quarter, more than tripling year-over-year. That's now 56% of total revenue, up from 49% just last quarter.

JORDAN: This company has essentially transformed into an AI infrastructure company that happens to also sell broadband chips and VMware software.

ALEX: Speaking of which, let's talk customers, because this is where it gets interesting. Broadcom has six custom AI chip customers, but Hock Tan really zeroed in on four: Google, Anthropic, OpenAI, and Meta.

JORDAN: The Google relationship is the elder statesman here—a decade of TPU development, and they just signed a long-term deal for "multi-tens of billions of dollars" of TPUs annually. They shipped the new Ironwood TPU v7 this quarter and are already ramping the next-gen v8i.

ALEX: But the real headline is Anthropic. Tan said Anthropic is on track to become Broadcom's largest XPU customer in 2027, deploying 5 gigawatts of TPU v8i next year and then 10 more gigawatts in 2028.

JORDAN: And OpenAI isn't far behind—their custom chip, nicknamed Jalapeño, is already reportedly outperforming Nvidia's Grace Blackwell in inference workloads at, according to Tan, less than half the cost. OpenAI's on pace for over 5 gigawatts by 2028, making them Broadcom's second-largest customer.

ALEX: That "half the cost" line is the thesis of the whole call, honestly. Custom silicon, co-designed for a specific model's workload, beats a general-purpose GPU on performance and cost. That's Broadcom's pitch to the market.

JORDAN: Now let's talk about the number that got everyone's attention: guidance. Q4 AI revenue guided to $21.7 billion, up 236% year-on-year. Full fiscal 2026 AI revenue now expected at $58 billion.

ALEX: And then they went further than usual—giving multi-year guidance. AI revenue is expected to double to $115 billion in fiscal 2027, then double again to $230 billion in fiscal 2028.

JORDAN: That's an unusually bold move for a company to lock in two years out. And CFO Amie Thuener was clear they don't plan to update it quarterly—so this is a stake in the ground, not a rolling estimate.

ALEX: On the Q&A, analysts pushed hard on whether that's really achievable. Stacy Rasgon from Bernstein did some math on gigawatts versus dollars, and Tan clarified something important: not all the gigawatt capacity they've outlined will necessarily be "deployed" in that window—some of it depends on data centers, power, and shells being physically r

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