Prediction: These 3 Stocks Will Be the Best Performers Over the Next 3 Years

Nvidia projects $1 trillion in lifetime sales for its Rubin and Blackwell GPUs by end-2027, citing $216B revenue in 2025 and ~ $370B Street estimates for the coming year, and expects global data-center capex to rise to $3–4T annually by 2030. Broadcom forecasts $100B in sales for its custom AI-chip division by 2027 after that division generated $8.4B in Q1 FY2026 (ending Feb. 1). Nebius expects ARR to jump from $1.25B in 2025 to $7–9B in 2026 via Nvidia partnerships and hyperscaler deployments; the article is highly bullish on all three names and discloses the author holds positions in Nvidia, Broadcom and Nebius.

Analysis

The current narrative discounts how the hardware layer will bifurcate: flexible, general-purpose accelerators will retain command of training and model experimentation while highly optimized inference ASICs will pressure price and marginal returns on deployed compute. That bifurcation amplifies winners beyond chip designers — HBM suppliers, advanced packaging vendors, and data-center power/cooling providers face multi-year demand volatility as customers trade off density versus unit economics. Expect a two- to three-quarter lead/lag in component shortages (HBM, substrates, test capacity) whenever a new architecture ramps, creating opportunities for suppliers with spare capacity and pinch points for those that don’t.

Key tactical risks sit at the interface of software and procurement. Model-level efficiency gains (quantization, distillation, sparse attention) can reduce raw FLOP demand by 20–40% over 12–36 months, materially compressing the implied TAM if hyperscalers prioritize cost-per-inference. Equally important, hyperscalers’ internal silicon programs are a 12–24 month asymmetric risk: a single large vertical choosing in-house ASICs can wipe out outsized share for a vendor on that customer’s footprints, producing lumpy revenue and margin volatility—even as headline industry capex remains large.

Consensus is underestimating execution risk at small infrastructure providers and overestimating persistent pricing power at the top of the stack. For smaller-cap cloud partners, valuation often embeds near-certain capacity monetization; a 30–50% execution discount is prudent until repeatable long-term contracts are visible. For incumbents, software/platform lock-in (toolchains, libraries, ops) is the true moat worth paying for, and investors should differentiate hardware-only growth from durable platform-led revenue when sizing positions.

Key Decisions for Investors

• NVDA: Core long for 12–18 months sized 2–4% of portfolio with risk-defined hedge — buy stock and purchase a 3–6 month 10–15% OTM put (or buy a debit put spread) to cap a single-quarter downside. R/R: asymmetric upside (30–60% if enterprise adoption and model scale continue) versus limited, pre-defined downside equal to put cost plus stock drawdown.
• AVGO: Tactical long via 9–12 month call-debit spread or stock for 12–24 months (size 2–3%). Rationale: capture premium on custom ASIC traction with lower volatility than pure GPU names. R/R: target 25–50% upside if design wins scale; downside 20–30% if hyperscaler ramp stalls—use spreads to limit carry cost.
• NBIS: Speculative growth play — allocate no more than 1–1.5% of portfolio and express via longer-dated LEAP calls or small equity position with a 30–40% stop. Rationale: high execution risk but >3x upside if capacity fills and ASPs hold; downside is near-total loss on execution miss, so position sizing must be conservative.
• Relative pair: Long AVGO / Short NBIS for 6–12 months (net neutral size ~1–2% of portfolio) to express conviction that bespoke ASICs will compress margin opportunity for third-party GPU-rental intermediaries. R/R: target 15–25% relative outperformance; risk is both names rerating higher if aggregate demand outstrips expectations.