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Nvidia pays $6 billion for Poolside’s model factory license

Nvidia has agreed to pay $6 billion for a non-exclusive license to Poolside’s Model Factory, an internal system used to build AI models, according to saastr.com.

Nvidia has agreed to pay $6 billion for a non-exclusive license to Poolside’s Model Factory, an internal system used to build AI models, according to saastr.com. Alongside this deal, Nvidia is investing $1 billion in Poolside at a $12 billion pre-money valuation. The three founders of Poolside will remain with the company, and 109 engineers have been offered positions to join Nvidia’s Nemotron project.

The deal followed Poolside’s failure to close a $2 billion funding round within a six-week window needed to pay for a 40,000 GB300 cluster scheduled to come online in January. Losing this funding led to the loss of access to the cluster. Nvidia’s investor letter clarified that the transaction is not an acquisition or acquihire but rather a licensing agreement combined with a significant investment. This move reflects Nvidia’s broader ecosystem spending spree in AI infrastructure and talent.

This transaction highlights the capital-intensive nature of AI infrastructure and the limits of venture capital funding even amid rapid AI market growth. Nvidia’s $6 billion payment for a license, rather than outright acquisition, signals a strategic approach to securing technology and talent without full ownership. The deal also underscores the competitive environment for AI model development platforms, where access to cutting-edge clusters and engineering teams is critical.

Poolside’s 40,000 GB300 cluster was expected to come online in January, but the funding shortfall prevented this. Nvidia’s $1 billion investment at a $12 billion valuation and the $6 billion license deal were announced this week, marking a major milestone in Nvidia’s AI infrastructure expansion.

Editorial standards. Reported and edited at Startupniti's news desk from the sources listed in the right rail. Every fact traces to a citation. If something looks wrong, write to corrections.
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