GPU Servers: Maximum Computing Power for AI, HPC and Visualization
GPU Servers Prices
Supermicro
SYS-A22GA-NBRT-G1 Supermicro SuperServer Dual Xeon 6960P 10U Server
Out of stock
Complete System Only
Supermicro
ARS-221GL-SR Supermicro Advanced Reference System (ARS) Grace (Arm) 2U Server
Out of stock
Complete System Only
Supermicro
SYS-422GS-NBRT-LCC Supermicro SuperServer Dual Xeon 6700 w/ P-cores 4U Server
Out of stock
Complete System Only
Supermicro
ARS-111GL-DSHR-LCC Supermicro Advanced Reference System (ARS) Grace (Arm) 1U Server
Out of stock
Complete System Only
Supermicro
SYS-422GS-NB3RT-LCC Supermicro SuperServer Dual Xeon 6700 w/ P-cores 4U Server
Out of stock
Complete System Only
Supermicro
SYS-421GE-NBRT-LCC Supermicro SuperServer Dual Xeon Scalable 4th Gen 4U Server
Out of stock
Complete System Only
Supermicro
SYS-511E-WR Supermicro SuperServer Single Xeon Scalable 5th Gen 1U Server
Out of stock
Complete System Only
Gigabyte
R263-SG0-AAL1 Gigabyte Single Xeon Scalable 4th Gen 2U 6NR263SG0DR000ABL1 Server Barebone
Out of stock
Supermicro
SYS-822GS-NB3RT Supermicro SuperServer Dual Xeon 6700 w/ P-cores 8U Server
Out of stock
Complete System Only
Supermicro
ARS-111GL-DNHR-LCC Supermicro Advanced Reference System (ARS) Grace (Arm) 1U Server
Out of stock
Complete System Only
Supermicro
ARS-111GL-NHR Supermicro Advanced Reference System (ARS) Grace (Arm) 1U Server
Out of stock
Complete System Only
Gigabyte
G493-SB2-AAP1 Gigabyte Dual Xeon Scalable 4th Gen 4U 6NG493SB2DR000AAP1 Server Barebone
Out of stock
Supermicro
SYS-751GE-TNRT-NV1 Supermicro SuperServer Dual Xeon Scalable 4th Gen 5U Server
Out of stock
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Frequently Asked Questions about Servers with GPU:
No. A GPU workstation is a desktop system designed for a single local user. A GPU server, on the other hand, is rack-mounted for data center use and offers features such as redundant power supplies, hot-swap components, and remote management (IPMI/BMC), which are essential for uninterrupted 24/7 operation in a multi-user environment.
Power delivery must be carefully planned. Each GPU has a specific power draw (TDP), which must be considered when sizing the power supply. Multi-GPU systems typically require redundant, high-efficiency power supplies (e.g., 80 PLUS Titanium) with sufficient capacity—often 2000W or more—to ensure stable operation under full load.
Technically, it is possible, but generally not recommended. For clustering and distributed computing tasks, using identical GPU models is critical to ensure consistent performance and avoid driver conflicts. Different models can lead to performance losses, as the system often operates at the pace of the slowest GPU.
Advanced cooling solutions are essential for high GPU-density servers. While traditional air cooling may suffice for systems with a few GPUs, multi-GPU setups under sustained load often benefit from direct-to-chip (D2C) liquid cooling solutions. These efficiently dissipate heat, enable higher and quieter performance, and extend component lifespan.
The choice of CPU should match the specific workload. For balanced system performance, processors with a high core count and strong single-thread performance, such as Intel Xeon or AMD EPYC series, are recommended. An adequate number of PCIe lanes is also crucial to ensure GPUs are fully connected and to prevent bottlenecks.
What to Consider When Choosing a GPU Server?
Not every GPU server is suitable for every application. When selecting a system, pay particular attention to the following points:
- Performance: Carefully consider which GPU architecture and model match your requirements. For highly compute-intensive tasks such as deep learning or high-performance computing, NVIDIA servers with CUDA and Tensor cores are often the preferred choice. Alternatively, AMD GPUs with their stream processors also deliver impressive performance for certain workloads.
- Technical Specifications: Check the size and type of graphics memory (VRAM) as well as its bandwidth. Sufficient VRAM is crucial for ensuring stable performance with complex workloads. The number of CUDA cores or equivalent units also significantly impacts the system’s parallel processing capabilities.
- System Requirements: GPU servers generate substantial heat and require a stable power supply. Make sure that both the power supply and cooling system are adequately dimensioned. The GPU’s form factor should also be compatible with the case and the motherboard – such as a GIGABYTE motherboard – to avoid installation issues.
- Application-Specific Features: Ensure that the chosen GPU provides all the necessary features for your applications—such as ray tracing, specialized Tensor cores for AI projects, or virtualization support. In certain scenarios, features like video transcoding or multi-GPU scaling may also be relevant.
Use Cases for GPU Servers
GPU servers are used in applications that require complex calculations and the processing of large datasets. Key use cases include:
- Deep Learning & AI: Professional GPUs significantly accelerate the training of complex neural networks. Their highly parallel processor architecture allows efficient processing of large datasets – which are ideally suited for backups on NAS drives such as the Seagate IronWolf –, which is essential for modern AI applications.
- Big Data Analytics: The parallel processing capabilities of GPUs, when combined with extremely fast storage devices such as a Samsung Enterprise SSD, enable the rapid analysis of large datasets. They can take over the workload of hundreds of conventional servers and, when paired with high-capacity enterprise hard drives such as the Seagate Exos, efficiently manage vast amounts of data, thereby saving both time and money.
- Rendering & Visualization: A high-performance GPU server is ideal for companies that create complex graphics, 3D models, or simulations. Industries such as architecture, media production, or game development benefit greatly from their power, with the huge project files often being stored centrally and securely on a Synology DiskStation.
- High-Performance Computing (HPC): HPC environments demand exceptionally high computing power, for example in material science simulations or climate modeling. Many companies rely on GPU support to perform calculations within acceptable time frames.
Server Hardware – Your Partner for High-Performance GPU Servers
Choosing the right GPU server is an investment in the future. With our GPUs, you benefit from high scalability, energy efficiency, and optimal performance.
- Bulk Order Discounts: Need multiple NVIDIA GPU servers or GPU systems? We offer exclusive price reductions for larger orders. The bigger your purchase, the greater your cost advantage.
- 24/7 Customer Support: Our experienced support team is available around the clock. Whether you need consultation, installation assistance, or technical support, we are always here for you.
- Free Shipping: We cover the shipping costs. Your GPU servers are delivered quickly and securely, so your IT projects can start without delay.
- Extended Warranty: Protect your investment long-term with up to 6 years of warranty coverage. In case of a defect, we provide fast and hassle-free replacement or repair at no extra cost.
- Certified Quality: Our company is ISO 9001:2015 certified, meaning our products meet the highest international quality standards. You receive powerful server solutions you can rely on at all times.
Whether for large language models, big data, or high-performance computing – whether you choose a Dell server, a Supermicro server or a completely customised configuration as your base, a powerful GPU server delivers tangible advantages. Rely on our top-tier hardware. Configure your GPU server now!