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AI server HPE ProLiant DL385 Gen10 – 2× NVIDIA A100 80 GB, 2× AMD EPYC 7502
HPE · AI and GPU servers
Made to order · we build the server, test it under load for 72 hours and usually deliver within 7–14 working days. We'll confirm the exact date after you order.
HPE ProLiant DL385 Gen10 server with 2× NVIDIA A100 80 GB (160 GB of graphics memory), two AMD EPYC 7502 processors and 512 GB of RAM. For training and fine-tuning AI models, running large language models and scientific computing. Delivered pre-installed for your task.
Full description, video and specificationsYour own chatbot, assistant or company document processing right on your premises. Which model will run on the server is determined mainly by the graphics memory (VRAM) – see the description below for details; we're happy to advise. Your data stays with you, with no monthly cloud fees.
Image and video generation in ComfyUI, rendering in Blender, or editing and effects in DaVinci Resolve. Each card can work on its own task.
When the server isn't running your workloads, it can mine cryptocurrencies on its graphics cards. For cards where we have current network data, you'll see today's earnings below.
| Component | Specification |
|---|---|
| Server | HPE ProLiant DL385 Gen10 (CTO), rack-mount |
| Graphics accelerators | 2× NVIDIA A100 80 GB HBM2e |
| Processors | 2× AMD EPYC 7502 (32C/64T each, 64C/128T in total) |
| Memory | 512 GB HPE DDR4 ECC |
| Drives | 2× 480 GB M.2 NVMe + 2× 1.6 TB enterprise SAS SSD; backplane for 8× 2.5″ SFF drives |
| Storage controller | HPE Smart Array S100i (RAID) |
| Network | 4× 1 GbE + 2× 10 GbE SFP+ |
| Power and management | 2× 1200 W, redundant HPE power supply (1+1), iLO 5 remote management |
| Condition | New – server and all components new |
| Power draw | approx. 1,200 W at full load (accelerators 2× 300 W, processors 2× 180 W) |
For companies, research teams and developers who need a lot of graphics memory on a single card – for training and fine-tuning models, running large language models and scientific computing. 160 GB of HBM2e memory is enough, for example, for Llama 3.3 70B in 8-bit quantisation with headroom for long context and multiple concurrent users. A100 accelerators can split each card into up to 7 separate instances (MIG), so several teams or jobs can work on the server in isolation. It is also suitable for rendering and big-data analytics.
We agree in advance what will run on the server (e.g. Ubuntu, NVIDIA drivers, CUDA, Docker, PyTorch, vLLM) and prepare it precisely for your task. Before handover, we test the server for 72 hours under full load. Standard configurations are usually delivered within 7–14 working days of quote approval, depending on component availability. We keep key spare parts in stock in Prague and provide on-site service and part replacement within 24/48 hours. The warranty is 24 months.
The server belongs in a rack in a server room or data centre. Don't want to deal with space, noise and cooling? We can place the server in our hosting at the data centre – terms agreed individually.