Why Isn’t NVIDIA Stock at $300 While Other Semiconductor Stocks Rally?

NVIDIA is up just 7% year to date at $199.64, lagging peer AI semiconductors such as Marvell (+95%), Micron (+69%), AMD (+43%), TSM (+26%), and Broadcom (+22%) as investors rotate into other AI exposure. The article highlights headwinds from NVIDIA's $4.9 trillion market cap, China export controls that stranded $4.5 billion of H20 inventory, and a broadening AI thesis across the semiconductor supply chain. Despite Q4 FY26 revenue of $68.13 billion, up 73% year over year, the stock fell 5% on the print and remains well below the implied $300 upside scenario.

Analysis

The market is signaling that AI monetization is no longer being rewarded as a single-stock narrative; capital is moving toward the names that monetize the buildout at different points in the stack. That is bullish for the entire capex ecosystem, but it also means NVDA is increasingly trading like a maturity/scale leader rather than a pure growth monopoly, so incremental upside becomes harder to justify on multiple expansion alone. The second-order effect is that every dollar diversified away from NVDA into custom silicon, memory, networking, and foundry exposure widens the relative-performance gap unless NVIDIA reaccelerates on something that changes the earnings path, not just beats a quarter.

The biggest overlooked issue is not demand—it is duration and geography. Export restrictions create a “stranded optionality” problem: product already built for a blocked market sits as an earnings drag until either policy changes or that inventory is re-routed, both of which are slow-moving. That puts a ceiling on near-term sentiment even if hyperscaler demand remains robust, because investors will discount the stock on policy uncertainty for months, not days.

The broadening of AI beneficiaries is likely still under-owned in portfolios, especially in names with more direct sensitivity to memory cycle normalization and custom accelerator ramp. MU and MRVL have more torque because their fundamentals can re-rate on both AI content growth and improved mix, while AVGO is becoming the cleanest way to own secular AI spend without single-customer concentration risk. TSM remains a lower-beta way to express the thesis, but it can lag if the market keeps rewarding visible AI revenue surprise over manufacturing leverage.

Consensus is probably still too anchored on NVIDIA as the default AI expression and not enough on the fact that the trade is becoming a basket. That is good for relative-value dispersion: the right question is not whether AI is over, but which balance sheets have the most incremental earnings surprise left. In that framework, NVDA can be fundamentally fine and still underperform for another 1-2 quarters while the rest of the supply chain catches up in public-market recognition.

Key Decisions for Investors

• Rotate from NVDA into a basket long MRVL/MU/AVGO against a smaller NVDA short or underweight for the next 4-8 weeks; this expresses continued AI capex with better relative upside as the market rewards second-order beneficiaries.
• Buy MU on pullbacks for a 3-6 month trade: the setup is attractive because memory pricing and cloud demand can both contribute to upside, creating asymmetric operating leverage if AI servers keep absorbing supply.
• Go long MRVL versus NVDA as a pair trade over 1-2 quarters; MRVL has more room for multiple expansion if custom silicon wins keep compounding, while NVDA remains exposed to policy and size-induced valuation drag.
• Use AVGO as the core large-cap AI compounder holding for 6-12 months; it offers broader AI exposure with less single-name concentration risk and should benefit if capex keeps diversifying across networking, custom logic, and software.
• For hedging, consider a short-dated NVDA put spread into the next catalyst window if the stock approaches recent highs; the risk/reward improves because upside is mathematically constrained while sentiment can still be pressured by export-control headlines.