
ABS Advanced 2U Server
AMD EPYC 9355P 32-core, 128GB, RAID6, NVIDIA RTX PRO 2000, redundant PSU
View on NeweggHighest performance
GPU-accelerated platforms purpose-built for artificial intelligence, generative AI and high performance computing.

Accelerated
Multiple PCIe Gen5 GPU slots for training and inference.
Scalable
Start with one server and grow into a GPU cluster.
Efficient
Power and cooling sized to rack power density.
Why AI Servers
Latest multi-core server CPUs paired with data center GPUs to speed up training, fine-tuning and inference.
High-efficiency redundant power supplies and cooling designed to run dense GPU nodes reliably.
High-speed networking and flexible storage make it easy to expand from one node to a cluster.
Choose GPU count, memory and storage to match model size and user demand.
Use Cases
Generative AI
Keep proprietary data in-house while delivering AI assistants to employees and customers.
Research & HPC
Run compute-heavy research workloads with GPU acceleration.
Computer vision
Process image and video datasets for inspection, safety and analytics.
Product Lineup

AMD EPYC 9355P 32-core, 128GB, RAID6, NVIDIA RTX PRO 2000, redundant PSU
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2x AMD EPYC 9575F 64-core, 256GB RAM, 960GB SSD, NVIDIA T4
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Dual Intel Xeon Scalable, 2U with 4x PCIe Gen5 GPUs
View on NeweggExact specifications vary by model and brand.
| Tier | Workloads | Form factor | Processor | Max memory | GPU / accelerators |
|---|---|---|---|---|---|
| Inference | AI inference, fine-tuning, VDI | 2U rack | 1–2 server CPUs | Up to 2 TB | Up to 4 GPUs |
| Training | Model training, GenAI, HPC | 4U rack | 2 server CPUs | Up to 4 TB | Up to 8 GPUs |
| Cluster | Large-scale training, multi-node HPC | Multi-node rack | 2 CPUs per node | Up to 4 TB per node | 8 GPUs per node |
Buy online, or request a volume quote through Newegg Business.
It depends on model size and the number of concurrent users. Inference for mid-size models often fits on 2–4 GPUs; training larger models typically needs 8 GPUs per node or more.
Many teams prototype on an AI workstation and move to AI servers for production. Both use the same software stack.
Multi-GPU servers draw significantly more power than general-purpose servers. Check rack power and cooling capacity before deployment.

Enterprise-grade rack servers with the performance, reliability and manageability that modern data centers demand.

Compact, efficient compute that processes data where it is created — from retail stores and factories to cell sites.

Multiple server nodes in a shared chassis to maximize compute per rack unit and reduce power, space and cabling.