Nebius: Lappeenranta, Finland

Latest Podcast Kalkkipaadenraitti 52-2
Planned
Future facility in planning stage
Operated by:

Nebius: Lappeenranta, Finland

Site planned for 2027 and has expansions through 2030

The Nebius data center campus in Lappeenranta, Finland, is a 310MW hyperscale AI facility being developed in partnership with Finnish firm Polarnode, with construction underway and phased operations expected to begin in 2027. Designed to support large-scale AI model training and application workloads, the multi-building campus represents one of the largest data center developments in Europe, backed by an estimated investment exceeding $10 billion. Located in southern Finland, the site leverages access to low-cost, renewable energy and a cold climate to optimize cooling efficiency, positioning it as a key anchor in Nebius’ expanding global AI infrastructure platform.

Map and Nearby Locations

Kalkkipaadenraitti 52-2
Nebius Sites
Nearby Facilities

Nebius: Lappeenranta, Finland Power Growth Over Time

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Construction
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Prospective
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across NN Request Dataset sites
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NN Request Dataset sites currently building
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NN Request Dataset sites announced, but haven't started construction

Sites within 15 miles of Nebius: Lappeenranta, Finland

Distance Site About
0.97 miles Polarnode: Lappeenranta
The Lappeenranta Data Center, developed by Polarnode, is a flagship industrial-scale project situated on a 33-hectare site in the Pajarila industrial area.
8.57 miles Neoen: Yllikkälä, Lappeenranta
This site, adjacent to Neoen's existing battery storage facility in Lappeenranta, is progressing through a municipal zoning process initiated at the developer's request. Construction is targeted for 2027–2028, pending permitting and grid connection.

Operating Company

Operated by:

The Nebius AI Cloud brings powerful full-stack infrastructure for AI developers and practitioners across startups, enterprises and science institutes to build and deploy generative AI applications and rapidly deliver scientific breakthroughs by training and running ML models within a secure, high-performance, and cost-optimized cloud environment.

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