Should You Forget Palantir and Buy These 2 Tech Stocks Instead?

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Palantir Technologies (NASDAQ: PLTR) has become one of the best performing stocks in the market this year, up more than 340% year to date as of this writing. However, the stock’s strong performance has also left it with one of the most hefty valuations in the space.

The stock now trades at an astronomical forward price-to-sales ratio (P/S) of about 49.5 times next year’s analyst estimates, while taking out its net cash position drops it to about 49.2 on an enterprise-value-to-sales multiple (EV/S).

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By comparison, at the height of software-as-a-service (SaaS) valuations, SaaS stocks traded at an EV/S multiple of 20 times with growth more than 30%. Palantir grew its revenue 30% last quarter.

The data analytics company established itself through its work with the U.S. government, where its platform helped perform mission critical tasks such as fighting terrorism and tracking COVID cases.

More recently, Palantir has been gaining strong momentum with its AI offering in the commercial space while its government business has also picked up. However, the company’s valuation has become pretty extreme, and even its top executives have been aggressively selling the stock the past few months, including its CEO and chairman.

Let’s look at two other fast-growing companies whose stocks trade at much lower valuations that could be alternatives to consider.

Like Palantir, Nvidia (NASDAQ: NVDA) has been a big winner this year, up about 190% year to date as of this writing. The company has also been growing its revenue quickly, including 94% last quarter.

Its stock trades at a forward price-to-earnings ratio (P/E) of about 32.6 based on 2025 analyst estimates. That’s quite a difference in valuation, as Nvidia’s forward P/E is lower than Palantir’s forward P/S ratio, so this is comparing earnings versus sales. Nvidia is growing revenue faster to boot.

Meanwhile, Nvidia is poised to keep benefiting from the ongoing artificial intelligence (AI) infrastructure build-out. Large tech companies continue to pour money into data centers to run AI applications and train large language models (LLMs). This is where Nvidia comes in, with its graphic processing units (GPUs) that have become the backbone of the computing power on which these AI models are being trained.

And in order for AI models to advance and become more sophisticated, they need exponentially more computing power on which to be trained. For example, the next-generation AI models from both Alphabet and Elon Musk-backed xAI are using 10 times as many GPUs for training than their prior versions. If companies are going to continue to race to create the best AI models, then Nvidia is going to continue to see a lot more demand for its GPUs.

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