Broadcom vs. Nvidia: 1 Critical Metric Shows Which Artificial Intelligence (AI) Chipmaker Is the Better Buy After Earnings

Broadcom’s fiscal Q3 AI semiconductor revenue surged 221% YoY to $16.7B, with total revenue up 86%, while Nvidia’s data center revenue (AI-exposed) grew 117% to $89B and overall revenue rose 106%. The article frames both as strong momentum stories, but suggests Nvidia screens cheaper on forward valuation (<20x next year’s earnings) versus Broadcom, implying Nvidia’s upside could be ~2x while Broadcom’s is “over 50%.” Overall, the tone is cautiously bullish on both, with incremental valuation-driven preference toward Nvidia.

Analysis

The market is likely underpricing the option value of custom silicon as a budget-optimization tool, not just a chip category. If hyperscalers keep moving a larger share of inference workloads to ASICs, the first-order loser is not necessarily NVIDIA’s absolute unit demand, but its pricing power and mix quality: GPUs remain the default for training, while the margin-rich “good enough” inference layer is the part most exposed to displacement. That is why the competitive read-through matters more for 6-18 months than for the next few trading sessions.

Near term, the tape should still favor AVGO because the story has cleaner scarcity value: fewer people can underwrite a bespoke design-win cycle than can extrapolate GPU demand. Over 1-3 months, the key catalyst is capex commentary from GOOGL/META and frontier labs; if they frame 2026 spending as more efficiency-driven, AVGO’s rerating can continue while NVDA’s multiple may compress even if fundamentals stay strong. AMD is the structural loser here: it sits in the least differentiated middle, with neither the software moat of NVDA nor the custom-design leverage of AVGO.

The contrarian risk is that the market may be overstating substitution. Custom chips tend to win narrow, repeatable inference workloads, but they do not erase the need for a flexible platform, so NVDA’s addressable market may shrink less than bears expect. What would falsify the AVGO-over-NVDA relative thesis is a sharp re-acceleration in NVDA pricing or any evidence that hyperscalers are pausing custom silicon ramps because of design, yield, or integration friction.

Key Decisions for Investors

• Tactically long AVGO into 1-3 month AI capex commentary, but size modestly: the upside is cleaner rerating on custom-silicon adoption, while the main risk is an order-ramp delay rather than outright demand loss.
• Pair trade: long AVGO / short AMD for 3-6 months. AMD is the weakest positioning asset because it lacks both the platform lock-in of NVDA and the bespoke customer intimacy of AVGO; this should work if hyperscalers keep optimizing inference cost.
• Do not short NVDA outright here; instead, use it as a relative-value hedge against AVGO or as a trim candidate on strength if hyperscaler disclosures tilt further toward internal ASICs.
• Watch GOOGL and META next capex updates as the best falsifier/confirmation signal. If they explicitly raise custom-silicon spend for 2026, add AVGO on weakness; if they re-center budgets on general-purpose accelerators, reduce the AVGO/NVDA relative trade.