Our GPU servers are assembled and prepared for shipment in Bulgaria.

This is where our team configures each system according to the customer’s selected hardware and workload requirements. After assembly, every server is powered on and carefully tested to verify the performance and stability of the GPUs, memory, storage, networking, cooling, and other critical components.

Before shipment, each system undergoes load testing and a final quality inspection. Only after all checks have been completed is the server securely packed and prepared for delivery.

All systems are shipped directly from Bulgaria. We work with international logistics partners to provide secure delivery to customers across Europe and other supported regions.

Worldwide shipping is available depending on the destination and order requirements.

Each product page includes an interactive configuration tool that allows you to build a server around your exact technical requirements.

You can select the required components directly on the page without requesting a manual quotation. As you modify the available options, the selected configuration and final price are updated automatically.

Depending on the server model, you can customize:

• AMD EPYC processor
• GPU model and quantity
• System memory
• NVMe storage
• Network connectivity
• Operating system
• Warranty coverage

Our configurator makes it easier to create a system for AI training, machine learning inference, 3D rendering, scientific research, virtualization, and other compute-intensive workloads.

Once you have selected the GPUs and main hardware components, the complete server configuration can usually be finalized within a few minutes.

Our GPU server platforms are designed to support a broad range of high-performance NVIDIA GPUs for AI, data center, rendering, and scientific computing applications.

Depending on the selected server model and configuration, available options may include:

• NVIDIA RTX 4090 AI
• NVIDIA RTX 5090 AI
• NVIDIA RTX 6000 Ada
• NVIDIA RTX 6000 PRO
• NVIDIA RTX 6000 PRO Blackwell Server Edition
• NVIDIA RTX 6000 PRO Blackwell Workstation Edition
• NVIDIA L40S
• NVIDIA H200 NVL

These GPU options are suitable for demanding workloads such as:

• Large language model training and fine-tuning
• AI inference and deployment
• Computer vision and image processing
• Scientific modelling and simulation
• 3D rendering and content creation
• Other GPU-accelerated computing tasks

GPU compatibility depends on factors such as chassis dimensions, power requirements, cooling capacity, PCIe connectivity, and the total number of cards installed.

Available models may vary based on stock, platform compatibility, and the selected server configuration.

GPU capacity varies depending on the selected server platform, chassis design, and overall hardware configuration.

Most of our systems are optimized for configurations with 4 to 8 GPUs. This range provides a strong balance between compute performance, cooling efficiency, PCIe connectivity, storage capacity, and networking options.

Available platforms include:

• 4U-E10G-ROMEX2 — supports configurations with up to 8 GPUs
• 4U-E10G-GENOAX2 — supports configurations with up to 8 GPUs
• 4U-E12G-ROME — supports configurations with up to 12 GPUs

Some platforms may technically accommodate additional GPUs through PCIe expansion hardware. However, installing a very high number of GPUs can reduce the PCIe resources available for NVMe drives, high-speed network adapters, and other components.

For most AI, rendering, and high-performance computing workloads, a configuration with up to 8 GPUs offers the most practical combination of performance, flexibility, and expandability.

Larger computing environments can be scaled more efficiently by deploying multiple GPU servers instead of placing the maximum possible number of GPUs in a single system.

A GPU server’s total power consumption is determined mainly by the GPU model, the number of installed cards, and the remaining system components.

As a general estimate, an 8-GPU server may require:

Configuration Estimated System Power

8 × NVIDIA RTX 4090 AI approximately 3–4 kW
8 × NVIDIA RTX 5090 AI approximately 4–5 kW
8 × NVIDIA RTX 6000 PRO approximately 3–4 kW
8 × NVIDIA H200 NVL approximately 5–6 kW

These figures are indicative rather than guaranteed. Actual consumption can vary depending on the processor, memory, storage, networking hardware, power limits, and workload intensity.

For multi-server installations, both rack-level power availability and cooling capacity must be planned carefully. Several high-density GPU systems operating in the same rack can place significant demand on the data center’s electrical and thermal infrastructure.

We can assist with estimating total power draw, cooling requirements, rack density, and suitable power distribution for larger deployments.

Selected platforms also support higher-density GPU configurations. For example, the 4U-E12G-ROME platform can accommodate:

• Up to 12 dual-slot GPUs using PCIe 4.0 x8 connections
• Up to 6 larger 3.5-slot GPUs using PCIe 4.0 x16 connections

The chassis uses high-capacity airflow for actively cooled GPUs, helping maintain stable operating temperatures in dense configurations.

Final power requirements are calculated individually based on the selected GPU models and complete server configuration.

Our systems are built for demanding workloads that benefit from high levels of parallel GPU processing.

Common applications include:

• AI model training and fine-tuning
• Large language model deployment
• Machine learning development and research
• High-throughput inference services
• Computer vision and image processing
• Scientific simulations and data analysis
• 3D rendering and visual production
• Other GPU-accelerated applications

Each platform is engineered to provide high GPU density, reliable PCIe connectivity, efficient cooling, and stable performance during continuous operation.

The final configuration can be adapted to the specific requirements of the workload, including GPU memory, compute capacity, storage performance, networking speed, and expected operating load.

The production and delivery timeline depends on the selected components, order quantity, and current hardware availability.

Standard configurations are typically assembled, tested, and dispatched within two to four weeks after the order has been confirmed.

Custom builds, larger deployments, or systems requiring specialized GPUs and components may need additional preparation time.

A more accurate lead-time estimate can be provided once the complete server configuration and delivery destination are confirmed.

Yes. Your configured server can be shipped directly to a colocation facility, hosting provider, or private data center.

Before dispatch, the system is assembled, tested, and prepared for installation. Depending on the selected configuration, the shipment may include:

• Rack mounting rails
• Compatible power cables
• Pre-installed operating system, when requested
• Basic system and network configuration

This reduces the amount of on-site preparation required and allows the data center team to install the server and bring it online more efficiently.

The delivery address, receiving instructions, contact details, and any facility-specific requirements should be provided before the order is shipped.