The competition to develop artificial intelligence models is intensifying.
Palantir Technologies (PLTR) seems to be getting more and more comfortable with that.
Instead of betting the firm on a single large language model, Palantir is building its artificial intelligence platform, or AIP, to work with models from competing AI companies while also connecting them to corporate data, permissions and real-world workflows.
That strategy became more obvious on Sept. 24.
Palantir has made xAI’s Grok 4.7 available to eligible AIP commercial customers. It also added on the same day, OpenAI’s GPT-6 Sol, GPT-6 Luna and GPT-6 Astra, and DeepSeek V4.1 Flash in some environments. In September, Palantir also added open-weight models from Z.ai and Moonshot AI, along with Google’s Gemini 3.8 Flash.
The collection is significant because Palantir doesn’t have to guess which AI lab will ultimately produce the most powerful model.
Its opportunity might be a layer higher: becoming the software companies use to work out which models can access their data, what they are allowed to do with it, and how AI gets dropped into real business operations.
This capability could become increasingly important as enterprises move from testing chatbots to deploying autonomous artificial intelligence systems.
Palantir wants AIP to sit above the AI model wars
Palantir has demonstrated how methodically it is growing the number of models that can run inside AIP with the September releases.
Grok 4.7 was added for eligible commercial environments with xAI enabled. OpenAI’s newest models are now available through OpenAI and Azure OpenAI integrations. Palantir also opened access to models from Google, Anthropic, DeepSeek, Z.ai, and Moonshot AI in several security environments.
This is a big deal.
A bank, manufacturer, or government agency may not want to rebuild its AI architecture each time a different model gets better at coding, reasoning, document analysis, or autonomous tasks.
Palantir is trying to make the model more replaceable while maintaining the customer’s underlying data, permissions, and operational structure.
Another September release builds on that idea.
Palantir announced general availability of AIP Evolve on Sept. 8. It orchestrates AI agents that can try to improve existing artificial intelligence systems. Goals can be reducing cost, reducing latency, improving evaluation scores, migrating workloads to different models etc. Then proposals can be reviewed before changes are merged into production, says Palantir.
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That means Palantir isn’t merely giving customers access to multiple AI models. It is also building software that helps decide when to change those models. CEO Alex Karp has made data control a central part of that pitch.
“Demand for AI sovereignty has now been unleashed,” Karp said when Palantir reported second-quarter results.
For Palantir, “sovereign AI” is only about clients preserving control of their unique data, models, infrastructure, and operational choices, instead of giving those benefits to an outside model supplier.
Now the approach is stretching well beyond Palantir’s own product.
Nvidia and Nebius deepen Palantir’s AI strategy
Palantir’s partnerships with Nvidia and Nebius are a glimpse into how the company wants this model-agnostic approach to work in practice.
Nvidia and Palantir announced a sovereign AI system for complex supply chains on Sept. 10, with an initial deployment inside Nvidia. By combining Nvidia’s open Nemotron models with Palantir Foundry, AIP and Palantir’s Ontology, supply chain information will be analyzed to help guide operational decisions.
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The Nvidia deployment is notable because one of the companies at the heart of the AI infrastructure boom is using Palantir’s software.
Nvidia said it has built a digital supply-chain command center using Palantir Foundry. The chip giant is also training Nemotron models on operational decisions and the reasoning behind them in an effort to codify expertise that previously lived with human planners.
Palantir named Nebius (NBIS) as its preferred sovereign-AI infrastructure partner just two days ago.
Palantir says that once integrated, eligible commercial customers will be able to access Nebius compute and inference infrastructure from within Palantir’s enterprise perimeter, which could give customers more control over their compute, data, and AI models.
The companies are also looking to speed up the deployment of AI compute capacity, including modular data centers in areas that already have power.
Palantir’s smartest AI bet may be avoiding one big bet
Palantir’s business growth gives the AI strategy more weight
Palantir’s AI strategy would be much easier to dismiss if it wasn’t showing up in the company’s financial results.
Second-quarter revenue surged 93% from a year earlier to $1.94 billion.
U.S. commercial revenue climbed 149% to $764 million, while U.S. government revenue increased 90% to $809 million. Total U.S. revenue reached $1.57 billion, up 115%.
Palantir also closed 220 deals worth at least $1 million during the quarter.
Of those, 98 were worth at least $5 million and 73 were worth at least $10 million.
U.S. commercial remaining deal value increased 124% to $6.24 billion, while U.S. commercial total contract value reached a record $2.13 billion, up 153%.
Profitability expanded alongside the growth.
Palantir generated $912 million of GAAP operating income, representing a 47% margin. Adjusted operating income was $1.19 billion, for a 62% margin.
The company subsequently raised its 2026 revenue forecast to between $8.15 billion and $8.158 billion and said U.S. commercial revenue should exceed $3.424 billion, representing growth of at least 134%.
Another major engine of growth is government spending.
On Sept. 17, the U.S. Army awarded Palantir USG a $48.1 million delivery order for software to replace nine legacy ammunition-management systems.
The initial term is 12 months and up to five optional additional years. The Army said the platform is intended to offer a single view of ammunition across planning, production, procurement, storage, distribution, and ultimate disposition.
That came just weeks after an Army milestone.
The Army has advanced the Tactical Intelligence Targeting Access Node, or TITAN, into production, with Palantir awarded $127 million in an initial eight-system production order.
Those awards together point to an unusual aspect of Palantir’s business.
Its rapidly growing commercial AI operation isn’t replacing its government business. Both are expanding at the same time.
Palantir’s biggest opportunity could depend on staying model-neutral
Valuation remains the big question for investors.
Palantir closed at $189.67 a share on Sept. 25. Wall Street remains broadly split on the value of the company’s unusually fast growth. Rosenblatt has a recent Buy and $225 target, while UBS reiterated a Buy and upped its target to $250 earlier this month. Other analysts are much more wary.
That disagreement shouldn’t be surprising.
Investors are trying to determine how much future AI adoption is priced into Palantir’s valuation, as the company posts revenue-growth rates rarely seen at its scale.
But do Palantir’s September product releases give investors another way to think about the company?
The best AI model might change again and again.
OpenAI might lead one category. Another category leader might be xAI, Google or Anthropic. Open-weight models could get a lot cheaper or a lot more powerful.
Palantir’s strategy seems increasingly constructed so that it does not necessarily have to know the winner beforehand.
If enterprises continue to adopt multiple models and want to maintain control of sensitive information and operational workflows, Palantir can try to sell the software layer that connects those pieces.
That may be the larger ambition behind what looked like a fairly simple product update on Sept. 24.
Palantir is not merely adding more AI models.
It is trying to make the identity of the winning AI model matter less to Palantir.
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