Palantir re-rates on a 149% U.S. commercial growth print
A 93% growth rate paired with a 62% adjusted operating margin is the combination the software market spent two years arguing was unavailable to anyone deploying AI at scale.
Palantir shares extended gains following a strong after-hours reaction to second-quarter results that delivered the cleanest validation yet of its commercial AI platform.
Revenue reached $1.935 billion, up 93% year over year and 19% sequentially. The standout was U.S. commercial revenue of $764 million, up 149% year over year and 28% quarter over quarter. U.S. government revenue grew 90% to $809 million.
The profitability line is the part that changes the argument
GAAP net income hit $1.062 billion, a 55% net margin. Adjusted operating margin reached 62%, the Rule of 40 score stood at 155%, and operating cash flow was $1.216 billion.
Those are not growth-company numbers with profitability promised later. A 93% growth rate paired with a 62% adjusted operating margin is the combination that the software market has spent two years arguing was unavailable to anyone deploying AI at scale, because inference cost was supposed to eat it. Here it did not.
Guidance embeds the acceleration rather than fading it
Management raised full-year 2026 revenue guidance to $8.150 billion to $8.158 billion, implying roughly 82% growth, and lifted U.S. commercial guidance to more than $3.424 billion, at least 134% growth. Third-quarter revenue is guided to $2.160 billion to $2.164 billion.
Total contract value closed in the quarter was $3.37 billion, with U.S. commercial TCV alone at $2.13 billion, up 153%. Contract value running ahead of recognised revenue is the detail that makes the guidance credible rather than aspirational.
The sovereignty argument
Chief executive Alex Karp framed the quarter around "AI sovereignty", arguing that enterprises are increasingly unwilling to hand operational control and proprietary data to frontier model providers. Palantir's positioning is as the operational layer that keeps decision systems inside the customer's environment.
Whatever one makes of the framing, it now has revenue behind it. The thesis moves from narrative to demonstrated scale: growth is no longer concentrated in government work, operating leverage has translated into reported profitability and cash generation, and the raised guidance carries the acceleration into the second half.
The re-rating reflects evidence that enterprise AI spend is converting into durable, high-margin revenue at a company that is not itself a model trainer. That last clause is the whole distinction, and it is why this print reads differently from the rest of the AI complex.