Nvidia and Perplexity AI Collaborate to Enhance European AI Models

Jun 11, 2025
Nvidia and Perplexity AI are partnering with European firms to develop localized AI models, leveraging Nvidia's DGX Cloud Lepton platform.

Nvidia and Perplexity AI have announced a collaboration to enhance AI capabilities in Europe by developing localized and sovereign AI models. This partnership involves working with over a dozen AI firms across Europe and the Middle East to refine AI technologies and distribute them to local businesses, announced in a press release.

The initiative aims to create AI models tailored to local languages and cultures, which will be integrated into Perplexity's platform. These models will be hosted on regional AI infrastructure provided by Nvidia's cloud partners, allowing businesses to access and customize them through an integration with Hugging Face.

Nvidia's DGX Cloud Lepton platform will play a crucial role in this collaboration, connecting AI developers with Nvidia's network of cloud providers. This setup will enable the training and deployment of AI models that reflect the unique linguistic and cultural characteristics of each European nation.

Perplexity AI's CEO, Aravind Srinivas, emphasized the importance of building custom AI solutions that cater to diverse needs and cultural preferences, reinforcing the company's commitment to a model-agnostic platform. The partnership is expected to boost Perplexity's presence in Europe, where Germany is already its second-largest market by revenue.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Daily AI Brief.

Also, consider following us on social media:

AI Brief AI Brief (X)
Free newsletter

Daily AI Brief

Daily report covering major AI developments and industry news, with both top stories and complete market updates

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.