3 Under-the-Radar Tech Stocks That Could Outperform the Nasdaq in 2026

The article is constructive on three AI infrastructure names, highlighting Iren’s $9.7 billion five-year Microsoft deal for 200 megawatts and $3.4 billion Nvidia deal for 60 megawatts, plus a 5-gigawatt pipeline and $3.7 billion in contracted annual recurring revenue expected by year-end. MaxLinear’s Q1 revenue rose 43% year over year, with infrastructure revenue up 35% sequentially and 136% year over year, while Q2 revenue is guided to $165 million at the midpoint. Innodata reported Q1 revenue of $90.1 million, up 54% year over year, and said a new undisclosed customer could contribute up to $51 million this year, supporting expectations for 40% revenue growth in 2026.

Analysis

The common trade here is not “AI” broadly; it is the monetization of bottlenecks. IREN is evolving from a pure capacity narrative into a higher-quality contract annuity story: once third-party software and orchestration are embedded, pricing power improves and customer churn falls, which matters more than headline megawatts. The market is still likely underappreciating that the real multiple expansion comes when contracted revenue is paired with operating leverage and geographic optionality, not just asset growth.

MXL is the cleaner second-order beneficiary because optical interconnects sit in the plumbing layer that scales with every new accelerator cluster. If sequential growth persists for one or two more quarters, the stock can re-rate faster than consensus because infrastructure suppliers often inflect before their end markets show up in reported capex. The risk is that investors extrapolate one strong quarter too far; any Q2 guide miss would quickly compress the “multi-year cycle” narrative and likely hit the name harder than the fundamentals justify.

INOD is the most asymmetric “picks-and-shovels” name, but also the most crowded conceptual trade because the market already recognizes data-as-training-infrastructure. The underappreciated point is customer diversification: a lower concentration profile reduces the discount rate on future revenue streams and can support a higher revenue multiple than peers with similarly fast growth. That said, this is still a procurement-driven business; if AI labs slow dataset spend after model training peaks, growth can decelerate abruptly over a 2-4 quarter horizon.

The contrarian angle is that the best risk/reward may not be the obvious winners themselves, but the enablers one layer down the stack. A basket long IREN/MXL/INOD versus a short in slower-moving legacy infrastructure or adjacent names with less direct AI exposure should capture the market’s tendency to overpay for visible AI demand while missing the infrastructure conversion path. The key catalyst window is the next 1-2 earnings prints: if sequential growth holds, these names can stay in momentum mode; if not, the market will punish forward multiples quickly.

Key Decisions for Investors

• Long IREN into the next earnings print / contract update; target a 3-6 month hold. Risk/reward is attractive if contracted ARR keeps compounding, but cut if management stalls on energization milestones or margin expansion.
• Long MXL on any post-earnings consolidation; use a 2-4 month horizon. Best setup is a momentum re-rating if Q2 sequential growth stays >15%, but size modestly because the stock likely trades sharply on guide confidence.
• Long INOD as a relative-growth compounder over 6-12 months; prefer pullbacks over strength. Upside comes from customer diversification and multiple expansion, but de-rate quickly if a single customer re-concentrates revenue.
• Pair trade: long MXL / short a slower-growth semiconductor infrastructure peer or basket with weaker AI linkage. Thesis is that bottleneck-enablers should outperform broader semi cyclicals over the next 1-2 quarters if sequential revenue stays hot.
• For higher-conviction risk, buy 3-6 month call spreads in IREN or MXL rather than outright equity. This captures the re-rating window while defining downside if the market decides the AI infrastructure cycle is already priced.