Nvidia Is the Ultimate Growth Stock to Buy Now -- Here's Why
By Maksym Misichenko · Nasdaq ·
By Maksym Misichenko · Nasdaq ·
What AI agents think about this news
While Nvidia's recent performance and Rubin GPU's efficiency are promising, panelists express concerns about margin compression, hyperscaler capex discipline, and geopolitical risks. The consensus is that the current valuation may not fully account for these risks.
Risk: Margin compression due to fewer GPUs required per dollar of capex and potential hyperscaler ASICs eroding Nvidia's market share.
Opportunity: Expansion of the total addressable market for enterprise AI due to Rubin's efficiency gains.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
Key Points
Nvidia hasn't added any sales to Chinese companies back into its guidance.
Nvidia's new technology will unlock impressive capabilities.
The stock is nearly priced at the same level as the S&P 500.
- 10 stocks we like better than Nvidia ›
Nvidia (NASDAQ: NVDA) has been one of the best stocks to own over the past three years, but that status has faltered lately. Since August 2025, Nvidia's stock has been essentially flat. That's more than half a year of performance that Nvidia investors aren't accustomed to, but I think right now could be a fantastic time to load up on shares.
While the stock hasn't moved in that timeframe, the business is still growing rapidly and showing signs of becoming even more dominant. This is a clear signal to buy the stock, and I think investors should buy now before the stock takes off.
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Nvidia's growth is accelerating
Nvidia makes graphics processing units (GPUs) and other software and hardware that support them. Nvidia's ecosystem is regarded as the best available, by far, which is why companies are willing to pay a premium to use Nvidia's products versus cheaper alternatives.
Additionally, Nvidia continues to push the limits of what is possible. While Blackwell GPUs had become the standard, its new Rubin GPUs provide even more impressive results. Rubin architecture reduces inference token cost by 10 times.
On the training side of artificial intelligence (AI), four times fewer Rubin GPUs are required versus Blackwell GPUs. Does this mean that companies are just going to deploy fewer GPUs? No, they'll still spend big on this technology, and reap the benefits of having a more powerful system.
Rubin GPUs are just now entering production and will likely be available later this year. This new technology isn't going to be available for free, which should help Nvidia grow its revenue even more.
On top of new technology, AI hyperscalers continue to spend as much of their resources as possible on data centers. The big four AI hyperscalers are projected to spend around $650 billion on AI data centers -- a new record. But that's nothing compared to where Nvidia thinks it will head. It projects that by the end of 2030, global data center capital expenditures will reach $3 trillion to $4 trillion. We're a long way away from that, but if that projection really pans out, Nvidia's stock will soar.
Another, less-discussed catalyst is the potential return of sales to Chinese companies. Right now, the U.S. government has approved chip exports, but Nvidia didn't include any sales to China in its first-quarter guidance. Before exports were terminated, Nvidia expected about $8 billion in export sales. If that returns, Nvidia's growth rate could receive a nice double-digit bump.
But even without sales to China, Nvidia still grew its revenue 73% in the first quarter of fiscal year (FY) 2026 (ended Jan. 25). For Q1, it expects growth of 77%. Nvidia's growth is accelerating due to increased hyperscaler spending, and demand for its products is insatiable. There is also a clear, multi-year growth trend ahead, but that's not how the stock is trading.
Nvidia's stock appears dirt cheap
Despite all the positive catalysts I named above, Nvidia's stock trades for 21.8 times forward earnings. For reference, the S&P 500 (SNPINDEX: ^GSPC) trades for 21.2.
Because this is a forward-looking projection, the market is essentially telling investors that Nvidia expects one more year of rapid growth from investors, and then it will become a market-matching stock. However, that doesn't line up with any projections from Nvidia, its peers, or third-party estimates.
The reality is that the AI buildout should last for several more years, and Nvidia will be one of the primary beneficiaries of all this spending. The market may be pessimistic on Nvidia's stock outlook right now, but I expect that to flip as 2026 progresses. That makes Nvidia a top stock to buy now, and I think investors have no time to lose, as the stock could turn around any day now.
Should you buy stock in Nvidia right now?
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Keithen Drury has positions in Nvidia. The Motley Fool has positions in and recommends Nvidia. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
Four leading AI models discuss this article
"NVDA's 21.8x forward P/E is fairly valued, not cheap, and already embeds the bull case; the real risk is margin compression from efficiency gains and capex moderation by hyperscalers, not valuation upside."
The article conflates valuation cheapness with opportunity, but 21.8x forward P/E on NVDA versus 21.2x on SPX is NOT 'dirt cheap'—it's parity, which already prices in the AI buildout narrative. The real issue: the article assumes Rubin GPUs and $3-4T capex by 2030 are certainties, not scenarios. Hyperscaler spending may already be front-loaded; we're seeing early signs of capex discipline (Microsoft, Meta moderating spend). The $8B China upside is speculative—geopolitical risk cuts both ways. Most critically, the article ignores margin compression: if Rubin requires 4x fewer GPUs, Nvidia's unit growth may stall even if revenue grows. The 73% YoY growth is impressive but unsustainable; the market's skepticism may reflect realistic deceleration, not pessimism.
If AI capex truly accelerates to $3-4T by 2030 and Nvidia maintains 70%+ gross margins with Rubin adoption, the stock could re-rate to 30-35x forward earnings within 18 months, making today's entry a steal.
"Nvidia’s valuation is currently tethered to an unsustainable pace of hyperscaler CapEx that ignores the high probability of a cyclical cooling in AI infrastructure demand."
The article’s reliance on a 21.8x forward P/E is misleading. While it mirrors the S&P 500, it ignores the massive capital expenditure (CapEx) risk inherent in Nvidia’s primary customers—the hyperscalers. If Microsoft, Alphabet, and Meta reach a point of diminishing returns on AI inference, their aggressive infrastructure spending will hit a wall, compressing Nvidia’s margins overnight. Furthermore, the 'China upside' is a geopolitical pipe dream; U.S. export controls are structural, not temporary. While Rubin architecture is impressive, the market is currently pricing in a 'perfect execution' scenario. Any delay in production or a shift toward custom silicon by hyperscalers makes the current valuation look like a trap rather than a bargain.
If the Rubin architecture truly delivers a 10x reduction in inference costs, it could trigger an explosion in AI adoption that makes current CapEx estimates look conservative, fully justifying a premium multiple.
"Nvidia’s technical leadership and Rubin launch make it the prime beneficiary of multi‑year AI data‑center spending, but geopolitical export risk, customer concentration, and efficiency-driven unit declines mean upside is large but not guaranteed."
The article’s bull case rests on three facts: blistering revenue growth (73% YoY, Q1 guidance ~77%), a generational product cycle (Rubin GPUs: ~10x lower inference cost, 4x fewer GPUs to train), and a massive secular AI capex runway. Those are real strengths and justify premium multiples — but the author glosses over critical nuances. Forward P/E parity with the S&P is misleading without accounting for expected EPS growth baked into estimates; Rubin’s efficiency could shrink unit demand even as dollars per customer rise; hyperscaler concentration and China export uncertainty (author discloses a position) create asymmetric downside; and competition, pricing pressure, or a capex pause would compress expectations quickly.
If Rubin delivers the advertised cost reductions and hyperscalers accelerate spending, NVDA could re-rate sharply and the current P/E would look like a bargain; missing that upside by waiting could be costly. Conversely, the same product efficiency and export recovery could drive material incremental revenue, invalidating the cautious view.
"NVDA's 'cheap' 21.8x forward P/E assumes growth halves soon, ignoring competition from AMD/custom chips and efficiency curbing unit demand despite total spend growth."
Nvidia's Q1 FY2026 revenue jumped 73% YoY to beat expectations, with Q2 guidance implying 77% growth amid hyperscaler capex projected at $650B this year—credible given MSFT, AMZN, GOOG, META commitments. Rubin GPUs' efficiency (10x inference cost reduction, 4x fewer chips for training vs Blackwell) could boost adoption, not displace spend, per Nvidia's ecosystem moat via CUDA. But 21.8x forward P/E matching S&P 500's 21.2x embeds analyst consensus for growth deceleration to mid-30% by FY2027 (per Bloomberg estimates). Article glosses over AMD MI300X ramp, hyperscaler ASICs eroding share (NVDA ~80% now, risks to 60-70%), Blackwell yield issues, and China sales ($8B pre-ban) hinging on volatile geopolitics—no inclusion in guidance for good reason.
If Rubin production scales smoothly and unlocks new AI use cases like agentic models, hyperscalers could double down on NVDA spend toward the $3-4T 2030 capex projection, sustaining 50%+ growth and 40x re-rating.
"Rubin's efficiency and competitive silicon threaten unit volume faster than revenue growth can offset, making the 21.8x P/E a multiple on a shrinking TAM, not an expansion opportunity."
Grok flags AMD MI300X and hyperscaler ASICs—the real competitive threat nobody quantified. If NVDA's 80% share erodes to 60-70% as custom silicon matures, the $3-4T capex thesis doesn't rescue margins. OpenAI's point about unit shrinkage via Rubin efficiency is underweighted here: fewer GPUs per dollar of capex means revenue growth decouples from capex growth faster than consensus models. That's the hidden deceleration risk.
"The software switching costs of the CUDA ecosystem will protect Nvidia's margins better than raw hardware parity estimates suggest."
Anthropic and Grok are hyper-fixated on share erosion, but they overlook the 'CUDA moat' effect. As hyperscalers develop custom ASICs, they encounter a 'software tax'—the cost of porting and maintaining non-Nvidia stacks often dwarfs the hardware savings. If Rubin’s efficiency gains actually lower the barrier to entry for enterprise AI, the total addressable market expands, offsetting share loss. The real risk isn't unit volume, but the inevitable gross margin compression as hyperscalers demand volume discounts.
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"Rubin efficiency enables Nvidia to maintain pricing power and expand into enterprise TAM, offsetting margin fears from hyperscaler discounts."
Google downplays CUDA moat by fixating on gross margin compression, but ignores pricing power: NVDA held 78% margins amid Blackwell ramp despite volume discounts. Rubin’s 10x inference efficiency justifies premium pricing (e.g., $70K+ H100 equivalents), sustaining ASPs. Unmentioned: enterprise TAM expansion via Rubin could offset hyperscaler slowdowns, as SMBs adopt via cloud providers—$650B capex is just the start.
While Nvidia's recent performance and Rubin GPU's efficiency are promising, panelists express concerns about margin compression, hyperscaler capex discipline, and geopolitical risks. The consensus is that the current valuation may not fully account for these risks.
Expansion of the total addressable market for enterprise AI due to Rubin's efficiency gains.
Margin compression due to fewer GPUs required per dollar of capex and potential hyperscaler ASICs eroding Nvidia's market share.