Nvidia's Rubin Chip Arrives in Late 2026. Is Now the Time to Buy This Artificial Intelligence (AI) Stock?

Nvidia (NVDA +0.79%) has dominated the artificial intelligence (AI) data center market with its GPU chips for years now. The AI era began with the Hopper microarchitecture, continued with Blackwell, and now looks to Rubin, Nvidia’s most ambitious chip platform yet.

The stakes are also arguably the highest that they’ve ever been. Not only has the market begun questioning AI hyperscalers for pouring hundreds of billions of dollars into data centers, but AI technology itself is evolving rapidly, creating a moving target for Nvidia and others.

Rubin is in full production to begin shipping later this year. Is now the time to buy Nvidia stock, or is the AI chip king about to lose its crown?

Image source: Nvidia.

Rubin represents a crucial upgrade amid a shift in AI technology

Nvidia specializes in GPU chips that excel at high-performance computing, such as training AI models. That’s still important as OpenAI and other AI companies develop more advanced models. But now, AI is quickly shifting toward inference. Deloitte Global predicted that compute for inference will overtake training this year.

OK, what does that mean?

Think of AI chips as engines in a car. A GPU’s raw power would be excellent for going very fast in a straight line, like in a drag race. But inference is a different type of compute, a different type of race. If it were a car, it would be the winding mountain roads that would require a more refined engine. In AI, inference compute involves strong, sustained reasoning capabilities for applications such as AI agents. In these situations, efficiency and speed trump raw maximum power.

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NASDAQ: NVDA

Nvidia

Today’s Change

(0.79%) $1.49

Current Price

$191.31

Key Data Points

Market Cap

$4.6T

Day’s Range

$189.58 - $193.95

52wk Range

$86.62 - $212.19

Volume

6.2M

Avg Vol

174M

Gross Margin

70.05%

Dividend Yield

0.02%

Rubin isn’t a single GPU; it’s six components, including CPUs and GPUs, networking switches and interfaces, that all work together as an AI supercomputer. Nvidia designed Rubin with inference in mind. The Vera Rubin NVL72 server rack-mounted superchip performs inference computing at 10% of the cost per million tokens compared to Nvidia’s current flagship Blackwell GB200 NVL72.

Nvidia should maintain its growth momentum

AI hyperscalers are getting pressure to begin realizing a return on their AI spending, and the drastic improvements in inference efficiency will likely be a strong selling point for Rubin. Nvidia announced back in November that it already had a $500 billion order backlog through 2026, and that is likely to grow further once it reports its latest earnings on Feb. 25. Just about every AI hyperscaler plans to spend even more on AI in 2026.

Data by YCharts.

Wall Street analysts certainly expect big things ahead for Nvidia. Estimates anticipate the company’s trailing-12-month sales of $187 billion increasing to approximately $327 billion this fiscal year, and $419 billion the following year. On top of that, Nvidia has beaten Wall Street’s quarterly revenue estimates for the past three years without fail, so it wouldn’t be a surprise if the actual numbers were even higher.

Is now the time to buy the stock?

Nvidia stock trades at nearly 25 times sales. If the company performs as expected, the stock gets much cheaper fairly quickly. Shares trade at just 11 times next year’s revenue estimate. It’s worth noting that Nvidia depends on a very concentrated customer base, and one or more hyperscalers backing off on their AI spending could quickly turn those estimates on their head.

Even though Nvidia still holds the lion’s share of the installed base of AI data center chips, it must continue to fend off competition, especially if customers place greater emphasis on cost savings. Broadcom has already had great success partnering with Alphabet on Tensor Processing Units (TPUs) for its AI models.

Nvidia will likely remain a long-term AI winner due to its entrenched leadership and the growth opportunities ahead for AI as a whole. However, investors may want to hold off, or at least keep buying to a nibble, until Nvidia updates shareholders on its latest outlook following earnings.