Nvidia vs. Broadcom: Which Trillion-Dollar AI Chip Stock Has More Upside After Their Latest Earnings?

Nvidia guided for roughly 70% fiscal-2028 revenue growth and $108 billion in current-quarter revenue despite supply constraints, while Broadcom expects AI semiconductor revenue of $58 billion in fiscal 2026, $115 billion in 2027, and $230 billion in 2028. Nvidia's data-center revenue reached $89 billion in Q2, up 117% year over year, supported by expanding CPU, software, hyperscaler, and enterprise demand. The article favors Nvidia over Broadcom because Nvidia trades at lower valuation multiples—about 23x forward P/E versus Broadcom's 31x—while offering a broader customer base and more comprehensive AI infrastructure platform.

Analysis

The investable distinction is not accelerator share but monetization durability: NVDA retains optionality across merchant compute, networking, systems, and software, whereas AVGO’s incremental AI earnings depend on a small number of customers converting design wins into sustained wafer starts. Custom ASIC adoption can lower customer unit costs, but it also shifts development expense and volume-commitment risk back toward the hyperscaler; any pause in frontier-model spending therefore hits AVGO’s revenue concentration harder than NVDA’s broader installed base.

A long NVDA/short AVGO relative-value position is attractive over the next 1-3 quarters if both names remain priced for exceptional growth. The valuation premium for AVGO leaves little room for schedule slippage, lower-than-expected custom-chip utilization, or customer insourcing; NVDA can absorb some mix shift into ASICs if total cluster spending, networking attach, and enterprise/sovereign demand remain resilient. The second-order beneficiaries are HBM and advanced-packaging suppliers—MU and TSM—because both GPU and ASIC architectures intensify memory-bandwidth and packaging demand; this is a cleaner way to express aggregate AI capex than choosing the silicon winner.

The article’s specific product, revenue, and acquisition assertions require independent verification before sizing directional exposure. Near term, consensus may be underestimating supply-chain bottlenecks rather than demand: constrained HBM, CoWoS capacity, power availability, and data-center commissioning can defer revenue recognition while preserving backlog, creating volatile quarterly prints without invalidating the 6-18 month capex cycle. Falsification for the NVDA-over-AVGO thesis would be a material NVDA gross-margin reset from platform pricing pressure, coupled with AVGO demonstrating diversified ASIC customers and firm multiyear volume commitments rather than non-binding design-win commentary.

Key Decisions for Investors

• Initiate a 1-3 month market-neutral pair: long NVDA / short AVGO in equal dollar exposure. Target 10-15% relative outperformance; exit if NVDA guides data-center growth materially below consensus while AVGO raises committed AI revenue outlook with customer concentration declining.
• Add MU on pullbacks as a 6-12 month infrastructure bottleneck expression; HBM mix and pricing can create earnings leverage independent of whether GPUs or ASICs gain share. Risk: new capacity or weaker hyperscaler capex compresses memory pricing; reassess on HBM contract-price and inventory data.
• Use TSM as a 6-18 month diversified beneficiary of leading-edge logic and advanced packaging demand. Prefer phased entry around monthly revenue and capacity-utilization updates; thesis weakens if advanced-node utilization falls or major customers defer packaging allocations.
• Do not add outright AVGO exposure solely on long-range AI targets until management discloses binding customer commitments, prepayments, and ASIC gross-margin trajectory. Treat a reduction in customer concentration and evidence of recurring networking/software attach as the trigger for reconsidering the short leg.