3 E Network Launches Hardware Procurement Evaluation for Finnish AI Compute Center

HONG KONG, Sept. 29, 2026 (GLOBE NEWSWIRE) -- 3 E Network Technology Group Limited (Nasdaq: MASK) (the “Company” or “3 E Network”), a business-to-business (“B2B”) information technology (“IT”) business solutions provider, committed to becoming a next-generation artificial intelligence (“AI”) infrastructure solutions provider, today announced the initiation of a global vendor evaluation and Request for Proposal (“RFP”) process targeting high-density server clusters, liquid cooling infrastructure, and core networking equipment for its multi-megawatt AI compute center in Mikkeli, Finland. Following the recent release of the Mikkeli Data Center Blueprint, the finalization of multi-megawatt power parameters, and the establishment of compute distribution channels, this procurement process transitions the facility into the practical phase of physical hardware selection and deployment. To guide the supply chain procurement, the evaluation focuses on four technical requirements set out in the blueprint:

1. Implementing 120kW+ Rack Power Density and Direct-to-Chip Liquid Cooling Standards

To address the escalating Thermal Design Power in Large Language Model (“LLM”) training workloads, and in alignment with previously established thermal management objectives, 3 E Network requires that proposed thermal management solutions support rack power densities of 120kW and above (“120kW+”).

Given the physical constraints of traditional air-cooling architectures when managing next-generation high-power AI accelerators, this evaluation will prioritize advanced Direct-to-Chip liquid cooling technologies. By employing micro-channel cold plates affixed directly to the silicon core, this technology utilizes high specific heat capacity to manage primary component heat. This standard aims to mitigate localized thermal hotspots, maintain thermodynamic stability during extended training cycles, extend hardware operational life, and optimize the facility's overall Power Usage Effectiveness.

2. Evaluating Next-Gen GPU Architecture Compatibility and Non-Blocking Network Topologies

The RFP process prioritizes “architectural compatibility and stress-test reliability” as key evaluation metrics. The Company’s engineering teams are benchmarking technical requirements against the spatial, power delivery, and data throughput profiles of upcoming flagship AI accelerator architectures, including ecosystems based on Blackwell and Vera Rubin planning.

In line with the high-speed cluster objectives set in the blueprint, the Company has specified high-performance standards for low-latency and non-blocking interconnectivity. Addressing the intensive data interaction demands of LLM training, the evaluation will focus on 800G and above Ethernet and InfiniBand-class leaf-spine topology solutions, aiming to optimize internal data flows and ensure large-scale GPU nodes operate in a highly synchronized environment.

3. Deploying All-Flash NVMe Storage Clusters and Parallel File Systems

In the multimodal model landscape, data transfer efficiency is as vital as underlying computational power. To overcome Data Input/Output (“I/O”) bottlenecks during large-parameter model training and prevent GPU compute idle time, the Company has designated all-flash NVMe over Fabrics storage arrays and high-performance parallel file systems as standard procurement criteria.

This specification requires the storage architecture to deliver high read throughputs at the terabytes-per-second level with microsecond latency. Additionally, the system must support efficient, concurrent model checkpointing capabilities. This allows for the rapid preservation of extensive model state data, thereby effectively facilitating recovery from hardware interruptions, minimizing the loss of training progress, and maintaining the operational efficiency of compute assets.

4. Accommodating 48V DC Power Evolution to Support the Green Energy Architecture

To smoothly integrate with the facility’s green energy architecture and manage the significant transient power spikes associated with new-generation AI chips, 3 E Network requires rack-level power delivery infrastructure to be compatible with and capable of evolving toward a 48V Direct Current busbar architecture. Compared to traditional 12V setups, 48V power delivery lowers line current, which reduces transmission losses and improves end-to-end power conversion efficiency.

Concurrently, the accompanying intelligent Power Distribution Units must provide high conversion efficiency alongside integrated dynamic load balancing and precise energy monitoring. This intelligent power distribution design is intended to offer robust reliability for the underlying electrical grid when high-density clusters manage complex inference tasks or initiate large-scale training runs.

Strategic Outlook and Execution Plan

With the foundational power parameters and commercial distribution channels for the Finnish project established, 3 E Network’s management team views this core hardware evaluation as a crucial phase in translating the theoretical blueprint into physical infrastructure. By outlining technical specifications including the 120kW+ liquid cooling threshold, non-blocking networking, high-throughput I/O, and 48V power compatibility, the Company has communicated clear deployment requirements to the hardware supply chain. 3 E Network is focused on building a robust, industrial-grade technological platform to support the computational demands of large-scale AI models. In the subsequent evaluation period, the Company will engage in detailed technical discussions with selected vendors to finalize the infrastructure matrix selection, accelerating the capital expenditure rollout and the practical commissioning of the Finnish project.

About 3 E Network Technology Group Limited
3 E Network Technology Group Limited is a business-to-business (“B2B”) information technology (“IT”) business solutions provider committed to becoming a next-generation artificial intelligence (“AI”) infrastructure solutions provider. It upholds the industry consensus of “AI and energy symbiosis” and has a strong vision in the field of energy investment. The Company’s business comprises two main portfolios: the data center operation services portfolio and the software development portfolio. For more information, please visit the Company’s website at https://3emask.com/.

Forward-Looking Statements
Certain statements in this announcement are forward-looking statements. These forward-looking statements involve known and unknown risks and uncertainties and are based on the Company’s current expectations and projections about future events that the Company believes may affect its financial condition, results of operations, business strategy, and financial needs. Investors can identify these forward-looking statements by words or phrases such as “approximates,” “assesses,” “believes,” “hopes,” “expects,” “anticipates,” “estimates,” “projects,” “intends,” “plans,” “will,” “would,” “should,” “could,” “may” or similar expressions. The Company undertakes no obligation to update or revise publicly any forward-looking statements to reflect subsequent events or circumstances, or changes in its expectations, except as may be required by law. Although the Company believes that the expectations expressed in these forward-looking statements are reasonable, it cannot assure you that such expectations will turn out to be correct, and the Company cautions investors that actual results may differ materially from the anticipated results and encourages investors to review other factors that may affect the Company’s future results in the Company’s registration statement and other filings with the U.S. Securities and Exchange Commission.

For more information, please contact:

3 E Network Technology Group Limited
Investor Relations Department
Email: ird@3emask.com
Website: https://3emask.com/