Broadcom Vs. Nvidia: The Real Challenger and Champion Story in Chips

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By Alex Sirois Published

Quick Read

  • NVDA posted $82 billion in Q1 revenue, up 85%, while AVGO's AI semiconductor revenue surged 143% year over year.

  • Hock Tan guided Q3 AI revenue to $16 billion, projecting 200% year-over-year growth driven by custom ASIC demand from hyperscalers.

  • AVGO gained 40% over the past year versus NVDA's 22%, giving Broadcom's custom-chip pipeline more upside if hyperscalers keep insourcing silicon.

  • Don't wait: the analyst who called NVIDIA in 2010 just revealed his top 10 AI stocks. See the full list FREE now.

Broadcom Vs. Nvidia: The Real Challenger and Champion Story in Chips

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NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) and Broadcom (NASDAQ:AVGO) just closed earnings seasons that framed the AI chip war clearly. NVIDIA sells the standardized picks and shovels every hyperscaler needs. Broadcom builds the custom silicon those same hyperscalers hope will reduce their dependence on Jensen Huang’s platform.

The Champion Lapped the Field Again

NVIDIA’s Q1 FY2027 delivered $81.615 billion in revenue, up 85.23% year over year, with Data Center alone hitting $75.246 billion. Networking inside that segment climbed 199%, a number that matters more than the Blackwell 300 headlines. It shows CUDA has evolved into a rack-scale system story built on InfiniBand, NVLink, and Spectrum-X.

Huang framed it plainly: “The buildout of AI factories, the largest infrastructure expansion in human history, is accelerating at extraordinary speed.” Guidance for Q2 landed at $91.0 billion, excluding China. The CEO also sold 445,723 shares in mid-June.

Broadcom Turned the Challenger Story Into Real Numbers

Broadcom’s Q2 FY2026 posted $22.19 billion in revenue, up 47.9%. AI semiconductor revenue hit $10.80 billion, growing 143%. Hock Tan raised the bar: “in Q3 we expect semiconductor revenue from AI to grow over 200 percent year-over-year to $16.0 billion.”

That growth comes from custom ASICs for hyperscalers plus Ethernet AI switches that compete directly with NVIDIA’s InfiniBand. VMware adds a $7.18 billion software cushion NVIDIA lacks.

Business Driver NVIDIA Broadcom
Core AI Product Merchant GPUs (Blackwell, Rubin) Custom ASICs plus Ethernet networking
Customer Model Sell to everyone Bespoke chips for select hyperscalers
Margin Profile 75.0% non-GAAP gross margin 69% adjusted EBITDA margin

Standardized Muscle vs. Bespoke Silicon

NVIDIA’s bet is that AI workloads favor general-purpose accelerators wrapped in CUDA. Broadcom’s bet is that Meta, Google, and others will keep pouring capex into in-house designs to escape NVIDIA’s pricing power. The $100 billion AI sales goal by 2027 depends on that thesis.

Risks differ. NVIDIA carries $119.0 billion in supply commitments and zero China Data Center revenue. Broadcom carries heavy VMware debt and customer concentration risk.

The Next Six Months Will Test Both Theses

Watch whether NVIDIA’s Q2 print clears the $91 billion bar and whether networking growth stays triple-digit. For Broadcom, the $16.0 billion AI guide is the tell. Miss it and the custom-silicon narrative wobbles. Hit it and the challenger label starts looking generous.

Why I Slightly Prefer Broadcom From Here

For investors prioritizing the most established AI infrastructure exposure, NVIDIA remains the default reference point. Its 92.3% Data Center revenue mix is a moat, and analyst targets sit near $302.83. But I lean Broadcom. AVGO is up 40.44% over the past year against NVDA’s 22.21%, and its custom-chip pipeline gives more upside asymmetry if hyperscalers keep insourcing. If Huang’s platform stays untouchable through 2027, I will happily be wrong.

Contact [email protected] for any questions or corrections.

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About the Author Alex Sirois →

Alex Sirois is a financial writer with experience spanning both retail and institutional investing. He has written for InvestorPlace and held roles at BNY Mellon and Bernstein, giving him a perspective that bridges Main Street portfolios and Wall Street analysis.

Alex holds an MBA from George Washington University and has built his career across multiple industries, including e-commerce, education, and translation — a breadth of experience that informs how he breaks down complex financial topics for everyday investors. His writing is conversational, actionable, and grounded in long-term, buy-and-hold investing principles.

At 247 Wall St., Alex focuses on delivering analysis that is both accessible and useful, with a clear emphasis on helping readers make more informed decisions with their money.

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