Broadcom Tripled AI Chip Sales and the Stock Still Fell. Is AVGO the Nvidia Alternative Investors Missed?
Broadcom just posted AI chip growth that dwarfs nearly every semiconductor result this year, yet the stock sold off anyway. The real question is whether the...
AVGO's AI chip revenue surged 221% to $16.7 billion while management projects $230 billion in AI revenue by fiscal 2028.
NVDA dominates general-purpose AI compute at a 45 P/E, while AVGO's custom XPUs serve hyperscalers at a forward P/E near 20.
XPU co-design locks in hyperscalers because switching chips requires restarting a multi-year design cycle, creating durable switching costs.
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Broadcom ( NASDAQ:AVGO ) reported a quarter that, on the numbers, looks like one of the most consequential AI results of the year. AI semiconductor revenue reached $16.7 billion, up 221% year-on-year and 54% sequentially, and management raised the fiscal 2027 AI revenue outlook to roughly $115 billion, with fiscal 2028 pointing to $230 billion.
The post-earnings reaction was still negative, largely because the Q4 total revenue guide of about $34.8 billion landed close to, but not clearly above, consensus. The settled session closed down 0.66% at $367.24, with the sharper move happening in extended hours around the report.
Revenue came in at $29.591 billion, up 85.5% year-over-year, with non-GAAP EPS of $3.32 against a $3.2382 estimate. Operating margin expanded 240 basis points to 67.9%, and free cash flow was $13.665 billion, or 46% of revenue.
The market chose to trade the one line that disappointed: the Q4 top-line guide. That is the reasonable-sounding overreaction, because the disclosure that mattered more was the forward AI trajectory.
A custom AI accelerator, or XPU, is silicon co-designed with a specific hyperscaler for a specific model family. XPUs represented 73% of AI revenue and XPU shipments grew more than three and a half times year-on-year. Hock Tan put it directly: "When you co-develop a chip that is optimized for your particular LLM workloads, you will outperform any GPU."
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