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

Hardware selection is the next step for the Finnish project; capital expenditure rollout and commissioning remain ahead.

Rhea-AI Summary

3 E Network (MASK) launched a global vendor evaluation and request-for-proposal process for its multi-megawatt AI compute center in Mikkeli, Finland.

The process targets high-density server clusters, liquid cooling and core networking, with criteria for storage and power delivery. Cooling proposals must support rack power densities of 120kW and above. The evaluation also focuses on 800G and above networking and compatibility with an evolving 48V DC power architecture. Multi-megawatt power parameters have been finalized, and compute distribution channels have been established. The company plans technical discussions with vendors to finalize its infrastructure choices.

3 points · 0 major

PositiveiHow this balance works

How this balance works

Rhea-AI gives every point it takes from this document a weight. Minor counts 1, Moderate 3 and Major 9, so one Major point outweighs several Minor ones. The bar adds up the weights on each side, and when neither side holds more than 65% of the total the balance reads Mixed.

It reads the document as published, with the same rules for every company, and it does not look at what the market expected or at how the stock traded, so a point can be objectively good on a day the stock falls.

Rhea-AI Sentiment measures something else, the tone of the wording.

How the balance worksHow Sentiment works

0 major · 1 point

How the balance works

Positive

• Moderate pointVendor evaluation and RFP process launched for the Mikkeli AI compute center.
• Minor pointMulti-megawatt power parameters finalized for the Finnish project.
• Minor pointCompute distribution channels established for the Finnish project.

Negative

• Minor pointInfrastructure selection remains pending technical discussions with vendors.

Argus 15 min delay 5 alerts

+3.35% vs previous close $0.87 last price 8.6x rel. volume Open Argus

Details

Market Reaction – MASK

$0.80 – $0.89 Day Range

$3.11M Market Cap

On Sep 29, the day this news came out, the latest delayed price for MASK is 3.35% above the previous close. Our momentum scanner has recorded 5 alerts for this stock so far that day. The latest delayed price is $0.87. Relative volume is exceptionally heavy at 8.6x the average.

Data tracked by StockTitan Argus (15 min delayed). Upgrade to Gold for real-time data.

Market Context

The Sep 22 Mikkeli energy-architecture update recorded a 5.51% 24-hour rise and established project ...

Analysis

The Sep 22 Mikkeli energy-architecture update recorded a 5.51% 24-hour rise and established project power-design context; the current notice specified hardware requirements for that facility, without establishing a new price response.

Key Figures

Rack power density: 120kW+ Network bandwidth: 800G and above Rack power delivery: 48V DC

Rack power density

120kW+

Required threshold for proposed thermal-management solutions

Network bandwidth

800G and above

Ethernet and InfiniBand-class network solutions

Rack power delivery

48V DC

Compatibility target for the facility's busbar architecture

Previous AI Reports

2 past events · Latest: Sep 23

Same Type 2 events

1. Sep 23

   AI data center execution

   24h Move

   +3.1%

   Advanced formal RFPs for liquid-cooled, high-density computing infrastructure in Finland

2. Sep 22

   AI energy architecture

   24h Move

   +5.5%

   Defined the planned Finnish facility's multi-megawatt green-energy architecture and power-design framework

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Key Terms

request for proposal, thermal design power, direct-to-chip liquid cooling, power usage effectiveness, +2 more

6 terms

request for proposal technical

"Request for Proposal (“RFP”) process targeting high-density server clusters"

A request for proposal (RFP) is a formal document a company or organization issues to invite outside vendors to submit detailed bids for a project, product or service—think of it as asking several contractors to propose how they would build and price a job. For investors, RFPs matter because winning or responding to them can create new revenue, reveal strategic partnerships, or signal future costs and competitive positioning, all of which can affect a company’s growth and valuation.

thermal design power technical

"escalating Thermal Design Power in Large Language Model (“LLM”) training workloads"

Thermal design power (TDP) is a specification that estimates how much heat a processor or other electronic component will produce under typical heavy use, and thus how much cooling is required to keep it safe and running at full speed. For investors, TDP matters because it influences product design, energy consumption, cooling costs, device size and reliability—factors that affect manufacturing cost, consumer appeal and competitive positioning. Think of it as the size of the radiator needed for an engine: too small and performance suffers, too large and costs rise.

direct-to-chip liquid cooling technical

"prioritize advanced Direct-to-Chip liquid cooling technologies"

A cooling method that pumps liquid directly over the surface of a computer chip (processor or graphics unit) using a fitted plate, removing heat more efficiently than air or indirect systems. Think of it like a water jacket on an engine: keeping the hottest part cooler lets the equipment run faster, longer, and in a smaller space, which can lower energy and space costs and enable higher-performance products—factors that affect operating margins, capital needs, and adoption potential for companies and data centers.

power usage effectiveness technical

"optimize the facility's overall Power Usage Effectiveness"

Power usage effectiveness (PUE) is a simple ratio that compares the total energy a facility uses (cooling, lighting, power losses) to the energy used directly by computing equipment; a lower number means more of the power is doing productive work. For investors, PUE acts like a fuel-efficiency rating for data centers — better PUE usually means lower operating costs, smaller environmental footprint, and a competitive advantage when scaling operations or meeting sustainability expectations.

nvme over fabrics technical

"all-flash NVMe over Fabrics storage arrays"

A network protocol that lets computers access high-speed NVMe solid-state drives (SSDs) across a data network as if those drives were directly attached to the computer. Think of it as a fast highway and clear rules that let distant storage behave like local storage, reducing delay and increasing throughput; it matters to investors because it affects the performance, scalability, and cost structure of data centers, cloud services, and companies that build storage hardware or networking equipment.

power distribution units technical

"the accompanying intelligent Power Distribution Units must provide high conversion efficiency"

Power distribution units are devices that deliver and manage electrical power to multiple pieces of equipment in data centers, server rooms, and industrial facilities. Think of them as an industrial-grade, intelligent power strip that helps prevent outages, balance loads, monitor consumption and enable remote control; their reliability and efficiency affect operational uptime, energy costs and capital planning, making them important to investors assessing infrastructure risk and operating margins.

AI-generated analysis. How Rhea-AI works. Not financial advice.

See more from StockTitan in Google Search and AI answers. Adds StockTitan as a preferred source · opens Google

Add on Google Not now

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/

FAQ

AI-generated questions and answers. How Rhea-AI works. Not financial advice.

What hardware is 3 E Network evaluating for its Mikkeli AI compute center?

3 E Network is evaluating high-density server clusters, liquid cooling infrastructure and core networking equipment. Its procurement criteria also cover all-flash storage, parallel file systems and rack-level power delivery for the planned facility.