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Large Language ModelsAI Business & IndustryTHE DECODERPublished: Sep 10, 2026, 22:01 JST2 min read

Nvidia, Palantir team up to run supply chains with AI

Nvidia, Palantir team up to run supply chains with AI

3 Key Points

  1. What happened

    Nvidia and Palantir are partnering to run supply chains with AI, starting with Nvidia's own supply chain. A single Vera Rubin rack contains 1.3 million components.

  2. Why it matters

    Palantir is integrating open Nemotron models into its Foundry platform, so companies can fine-tune them with their own operational data. Nvidia cuOpt handles scenario planning and optimization.

  3. What to watch

    The system is designed to spot bottlenecks earlier, speed up material allocation, and evaluate alternatives. Decisions and outcomes feed back into the models so they improve over time.

WHO IT HITSManufacturing, pharma, and energy companies can run the full stack on their own hardware or in the cloud, potentially reducing dependence on third-party providers.

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Context & Analysis

Nvidia and Palantir are combining their strengths to bring AI to supply chain management, starting with Nvidia's own complex operation. Nvidia's supply chain involves millions of parts and thousands of suppliers, making it a demanding testing ground. The partnership integrates Palantir's Foundry platform with Nvidia's open Nemotron models and cuOpt optimization, aiming to create a system that learns from decisions to improve over time.

This move aligns with a broader trend of companies seeking to run their own AI models rather than relying on third-party providers. Palantir CEO Alex Karp has advocated for this approach, and Mistral founder Arthur Mensch recently made a similar argument. Nvidia has been developing its Nemotron lineup as an alternative to Chinese open-weight models, though the competitive landscape is shifting with new entrants like Thinking Machines Lab's Inkling.

The success of this partnership hinges on whether the integrated system can deliver tangible improvements in spotting bottlenecks and allocating materials. For manufacturers, pharmaceutical companies, and energy firms, the appeal lies in running the full stack on their own hardware or in the cloud, potentially giving them greater control over their data and operations. The involvement of infrastructure partners like Dell, Cisco, Rackspace, and Nebius suggests a robust support network, but the real test will be adoption and measurable outcomes.

FAQ
What is the first deployment target?
Nvidia's own supply chain, which spans millions of parts, thousands of suppliers, and a global partner network.
How can companies run the full stack?
Companies in manufacturing, pharma, or energy can run the full stack on their own hardware or in the cloud through the Sovereign AI OS reference architecture.
What infrastructure partners are involved?
Infrastructure partners include Dell, Cisco, Rackspace, and Nebius.

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