AI Servers: High-Performance Servers for Artificial Intelligence and Data-Intensive Workloads
AI Servers Prices
Supermicro
SYS-211E-FRDN2T Supermicro SuperServer Single Xeon Scalable 4th Gen 2U Server
Out of stock
Complete System Only
Supermicro
SYS-242B-NR Supermicro SuperServer 4 Socket Xeon 6700 w/ P-cores 2U Server
Out of stock
Complete System Only
Supermicro
SYS-212B-FN2T Supermicro SuperServer Single Xeon 6500 w/ P-cores 2U Server
Out of stock
Complete System Only
Gigabyte
G893-ZX1-AAX3 Gigabyte Dual Supports EPYC 8U 6NG893ZX1DR000ACX3 Server Barebone
Out of stock
Supermicro
SYS-821GE-TNHR-G1 Supermicro SuperServer Dual Xeon 8570 8U Server
Out of stock
Complete System Only
Gigabyte
R164-SG5-AAV1 Gigabyte Single Xeon 6 SoC 1U 6NR164SG5DR000AAV1 Server Barebone
Out of stock
Gigabyte
R263-S33-AAL1 Gigabyte Single Xeon Scalable 4th Gen 2U 6NR263S33DR000ABL1 Server Barebone
Out of stock
Gigabyte
E263-S30-AAD1 Gigabyte Single Xeon Scalable 4th Gen 2U 6NE263S30DR000ABD1 Server Barebone
Out of stock
Supermicro
SYS-322GA-NR Supermicro SuperServer Dual Xeon 6900 w/ P-cores 3U Server
Out of stock
Complete System Only
Gigabyte
G292-Z45 Gigabyte DualEPYC 7002 2U 6NG292Z45MR-00 Server Barebone
Out of stock
Supermicro
SYS-221HE-TNR Supermicro SuperServer Dual Xeon Scalable 5th Gen 2U Server
Out of stock
Complete System Only
Gigabyte
W753-W50-AA01 Gigabyte Single Xeon W-2400 6NW753W50MR000AB01 Workstation Barebone
Out of stock
Supermicro
SBI-411E-1G Supermicro SuperBlade Single Xeon Scalable 4th Gen 8U Server
Out of stock
Complete System Only
Supermicro
SYS-A22GA-NBRT Supermicro SuperServer Dual Xeon 6900 w/ P-cores 10U Server
Out of stock
Complete System Only
Gigabyte
G493-ZB1-AAP1 Gigabyte Dual EPYC 9004 4U 6NG493ZB1DR000ACP1 Server Barebone
Out of stock
Supermicro
SYS-821GE-TNHR Supermicro SuperServer Dual Xeon Scalable 4th Gen 8U Server
Out of stock
Complete System OnlyCan't find the right product from "AI Servers"?
Frequently Asked Questions about Servers for AI:
AI Server systems should be equipped as follows:
- NVMe SSDs (PCIe Gen4 or Gen5) – For training large models with random data access patterns, e.g., image or video analytics.
- RAID-10 Arrays – Combining high read/write performance with redundancy.
- Storage Tiers – Cold data (HDD), hot data (NVMe), and buffer (RAM) to optimize cost and performance.
GPU architecture significantly impacts parallelization capabilities and memory bandwidth. Modern GPUs like NVIDIA A100/H100 provide Tensor Cores for matrix operations, HBM2e/3 memory with up to 1.25 TB/s bandwidth, and NVLink/NVSwitch for fast GPU-to-GPU communication. This enables large models to be distributed efficiently and dramatically reduces training times, especially in multi-GPU setups.
CPUs in AI Servers mainly orchestrate data flows, handle I/O, and perform preprocessing. Key factors include:
- High I/O Connectivity (PCIe 4.0/5.0 with 64+ lanes) for connecting multiple GPUs or NVMe devices.
- Large L3 Cache and High Core Counts (at least 32–96 cores for AMD EPYC / Intel Xeon Scalable Gen 4).
- CCX Architecture and NUMA Control to efficiently manage memory locality and data coherence.
The number and configuration of GPUs depend on model size, batch size, and parallelization strategy. Inference workloads can often be handled with a single GPU, while training large language models (LLMs) typically requires 4 to 8 GPUs connected via NVLink. Selection is guided by benchmarks and scaling tests to balance cost and performance effectively.
Servers for Machine Learning vs. Servers for AI: Choosing the Right Solution
AI Servers form the foundation of modern data-driven applications – from predictive models to complex neural networks. Depending on the use case, the requirements for these servers differ significantly: traditional machine learning workloads often suffice with CPU-based systems, while deep learning applications rely on GPU-accelerated servers. Learn more about the differences below:
Servers for Machine Learning for Analysis and Training
A Server for Machine Learning is the ideal platform for data science teams and a wide range of workloads. It is ideal for training traditional models (e.g. regressions, random forests, gradient boosting) as well as for resource-intensive data preparation and analysis, with the vast amounts of raw data often stored on durable enterprise-class hard drives such as the Seagate Exos. These servers can easily be combined with powerful CPUs and one or more enterprise GPUs. This setup provides the flexibility needed to efficiently handle both CPU-intensive preprocessing tasks and GPU-accelerated model training.
Servers for AI for Maximum Performance
Servers for AI are specifically designed for training large neural networks that demand massive computing power, such as large language models or image and video analysis. These systems, often based on a GIGABYTE motherboard specifically designed for multi-GPU setups, are uncompromisingly engineered for maximum performance and GPU density, and form the foundation of high-performance computing (HPC) in the field of AI. They typically feature multiple GPUs connected directly via high-speed interconnects like NVIDIA NVLink.
AI Server: The Right Hardware for Your AI Requirements
Selecting the right hardware is crucial for running AI applications efficiently and reliably. It’s not just about raw performance but also about a balanced interplay of CPU, GPU, memory, and network interfaces. Our AI Servers are precisely engineered to meet the complex demands of deep learning, machine learning, and other data-intensive AI workloads.
- GPUs (e.g., NVIDIA A100, H100, or a high-performance AMD GPU, such as one from the Instinct series) – Enable massive parallel computation and significantly accelerate training compared to traditional CPUs.
- CPUs (Intel Xeon, AMD EPYC) – Provide stable control, data preprocessing, and GPU workload management – powerful, efficient, and durable.
- Large Memory (up to 4 TB RAM) – Essential for holding large AI models in memory, such as NLP or image processing applications.
- High-Speed Storage (NVMe SSDs such as the Samsung Enterprise SSDs, RAID systems) – Ensures the data pipeline is never a bottleneck, allowing rapid access to training and evaluation datasets.
- Modular Chassis & Network (e.g., NVLink, InfiniBand) – For maximum scalability and performance, especially in distributed computing and cluster infrastructures.
Our server solutions can be customised to suit your needs – whether you require a single workstation for AI, are looking to use a traditional Dell server for your infrastructure, or wish to set up a complete data centre with high-density GPU nodes, such as a Supermicro server. Order your AI Server today!
Server Hardware – Your Partner for High-Performance AI Servers
As a specialized provider of professional servers, we know exactly what matters when selecting and procuring high-performance AI Servers. With our extensive experience and a broad range of premium servers, we offer solutions perfectly tailored to the needs of modern data centers and enterprises.
- ISO-certified quality (ISO 9001:2015)
- Fast & free shipping
- Non-binding quotation service
- Warranty extension up to 6 years
- Additional discounts for bulk orders
Don’t settle for standard solutions – rely on a server precisely optimized for your machine learning and deep learning workloads. Our experts will help you select the right GPUs, CPUs, and optimal memory hierarchy to maximize the performance of your AI Server.