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NVIDIA H200 · 141GB HBM3e · For AI training
NVIDIA H200 8-GPU servers for AI training, in Egypt & the UAE.
Eight NVIDIA H200 NVL GPUs linked by NVLink bridges, with 1,128GB of HBM3e, two 192-core AMD EPYC 9965 processors and 3TB of memory in one rack server: the system for training and fine-tuning large models on your own data, in your own data centre.
1,128GB of GPU memory
8 × H200 NVL with 141GB of HBM3e each, and 4.8 TB/s per GPU.
384 AMD EPYC cores, 3TB RAM
2 × AMD EPYC 9965 with 24 × 128GB DDR5-6400 memory.
1.6 Tb/s of networking
Four dual-port 200GbE QSFP56 network cards.
24-month NBD server warranty
Plus a 12-month replacement warranty on the GPUs, with burn-in testing and support from our engineers.
What it’s for
Built for the heaviest AI work.
When models are large, data is sensitive and training never stops, the H200 keeps everything on your own hardware.
Training and fine-tuning LLMs
Train and fully fine-tune large language models, including Arabic models, on your own data.
Very large models at full precision
Run the largest open models at 16-bit precision, with long contexts.
Pharma and life sciences
Protein structure prediction, molecular simulation and drug-discovery models.
Oil and gas
Seismic interpretation and reservoir models, kept on-premise.
Banks, telecoms and government
Private AI on data that cannot leave your network or the country.
Research and HPC
Scientific computing with 60 TFLOPS of FP64 Tensor Core performance per GPU.
Why the H200
More memory. More bandwidth. Fewer compromises.
141GB of HBM3e per GPU
Fit larger models and bigger batches on every GPU, with fewer workarounds.
4.8 TB/s memory bandwidth
Keeps the Tensor Cores fed for faster training and faster token generation.
3,341 TFLOPS of FP8
Per GPU, with sparsity, from Hopper Tensor Cores and the Transformer Engine.
Up to 7 MIG instances
Split each GPU into up to seven isolated 16.5GB instances for teams and smaller jobs.
NVLink bridges included
The GPUs are linked with NVLink bridges at 900GB/s per GPU, for models split across several GPUs.
Genuine NVIDIA part
Genuine NVIDIA H200 NVL 141GB boards, NVIDIA part number 900-21010-0040-000.
Specifications
NVIDIA H200 8-GPU server specifications.
The standard configuration of our NVIDIA H200 8-GPU server, with NVIDIA’s published GPU specifications. We can adjust processors, memory, storage and networking to your workload.
Server: NVIDIA H200 NVL 8-GPU Server
| GPUs | 8 × NVIDIA H200 NVL 141GB (PN 900-21010-0040-000), PCIe 5.0, with NVLink bridges |
|---|---|
| Total GPU memory | 1,128GB HBM3e |
| Processors | 2 × AMD EPYC 9965: 192 cores / 384 threads each, 2.25GHz, 384MB cache |
| Total CPU cores | 384 cores / 768 threads |
| System memory | 3TB: 24 × 128GB DDR5-6400 load-reduced ECC (LRDIMM) |
| RAID | Hardware RAID controller |
| Boot drives | 2 × 960GB SATA SSD, read-intensive (RAID 1) |
| Data drives | 4 × 7.68TB U.2 NVMe PCIe 4.0, read-intensive (RAID 5, about 23TB usable) |
| Networking | 4 × dual-port 200GbE QSFP56 PCIe low-profile NICs (8 × 200GbE) |
| Power | 4 × 3,200W Platinum power supplies |
| Warranty | 24-month Mega Build Up next-business-day (NBD) warranty on the server; 12-month replacement warranty on the GPUs |
Configurations can be adjusted to your workload. The final specification is confirmed on your quote.
GPU (per card): NVIDIA H200 NVL
| NVIDIA part number | 900-21010-0040-000 |
|---|---|
| Architecture | NVIDIA Hopper |
| GPU memory | 141GB HBM3e |
| Memory bandwidth | 4.8 TB/s |
| FP64 / FP64 Tensor Core | 30 / 60 TFLOPS |
| FP32 | 60 TFLOPS |
| TF32 Tensor Core | 835 TFLOPS* |
| BF16 / FP16 Tensor Core | 1,671 TFLOPS* |
| FP8 Tensor Core | 3,341 TFLOPS* |
| INT8 Tensor Core | 3,341 TOPS* |
| Multi-Instance GPU | Up to 7 MIGs @ 16.5GB |
| Interconnect | NVLink bridges included (2- or 4-way, 900GB/s per GPU); PCIe Gen5, 128GB/s |
| Decoders | 7 NVDEC, 7 JPEG |
| Max power | Up to 600W (configurable) |
| Form factor | PCIe, dual-slot, air-cooled |
| Confidential computing | Supported |
* With sparsity. NVIDIA lists these specifications as preliminary and subject to change.
How ordering works
From written quote to a running system.
01
Consult & quote
We size the system to your models and data, then send a written quote with exact NVIDIA part numbers, lead time, delivery terms and warranty.
02
Export checks
Data-centre GPUs are export-controlled, so we collect your end-user details and complete the paperwork before we confirm the order.
03
Source factory-new
New, sealed NVIDIA H200 NVL boards, with every serial number recorded on your delivery documents.
04
Build, test & install
Burn-in tested, then delivered, racked, cabled and powered on by our engineers.
05
Support for life
24-month NBD server warranty, 12-month GPU replacement, upgrades and expansion.
Compare our AI systems
From your desk to a full AI cluster.
For development
NVIDIA DGX Spark
128GB unified memory
On your desk · models of up to 200B parameters
For inference
RTX PRO 6000 Blackwell 8-GPU Server
768GB GPU memory
8 × 96GB GDDR7 · AI video, rendering and simulation
For training
NVIDIA H200 8-GPU Server
1,128GB GPU memory
8 × 141GB HBM3e · NVLink
You are here
What is the difference between the H200 and the RTX PRO 6000 Blackwell?
The H200 has 141GB of HBM3e per GPU, 4.8 TB/s of memory bandwidth and NVLink bridges, and is built for training and very large models. The RTX PRO 6000 Blackwell has 96GB of GDDR7 per GPU and is built for inference, AI video, rendering and simulation at a lower cost per GPU. See the RTX PRO 6000 8-GPU server.
How much power does an H200 8-GPU server need?
Each H200 NVL can draw up to 600W, so eight GPUs can draw up to 4.8kW before the rest of the server, which runs on four 3,200W Platinum power supplies. Plan for dedicated circuits, two power feeds and cooling sized for the load. Our engineers confirm the exact figures for your configuration.
Can it train Arabic language models?
Yes. The H200 runs the standard AI frameworks, so you can train or fine-tune Arabic and multilingual models on your own data, with enough memory for large models.
Can the GPUs be shared between teams?
Yes. Multi-Instance GPU (MIG) splits each H200 into up to seven isolated instances of 16.5GB, so several teams or jobs can share one server safely.
Do you deliver and install in Egypt and the UAE?
Yes. We deliver, rack, cable and power on the server at your office, data centre or colocation facility in Egypt or the UAE.
Can I buy H200 GPUs on their own?
Yes. We supply NVIDIA H200 NVL 141GB PCIe cards (part number 900-21010-0040-000) individually as well. We recommend a complete server, because we size, burn-in test and support the whole system, and it carries our 24-month NBD warranty. Cards bought on their own come with a 12-month Mega Build Up replacement warranty, followed by the manufacturer’s warranty.
How long does an H200 order take?
H200 GPUs and servers are sourced to order, so we don’t quote a fixed lead time online. Your written quote confirms the lead time, the delivery terms and who handles import customs, and we record the serial numbers of every GPU at delivery.
Can I return an H200 order?
No. H200 GPUs and servers are special-order items, so they can’t be returned once ordered. They are fully covered by their warranty if anything is faulty, and every server is burn-in tested before it leaves us.
What warranty and support do I get?
The server comes with a 24-month Mega Build Up next-business-day (NBD) warranty, and the GPUs with a 12-month replacement warranty. Our own engineers handle diagnosis and on-site support. See our warranty services.
How do I get a price?
Answer three quick questions in the form on this page. An engineer replies within 24 working hours with a recommended configuration and price.
Get a quote
Configure your H200 server.
Answer three quick questions and an engineer replies within 24 working hours with a recommended configuration and price.
- No obligation, no sales pressure
- Sized by an engineer, not a script
- 24-month NBD server warranty, 12-month GPU replacement
Step 1 of 3
Talk to an AI infrastructure engineer.
Call, WhatsApp or email our team and we’ll reply within 24 working hours.
