Size & source
Map your models, users, budget, and site requirements. Compare supplier configurations and confirm the exact bill of materials.
GPU accelerators / Hopper
NVIDIA H100.
Scope H100-based compute for model serving, development, and demanding AI workloads.
Configuration, availability, and commercial terms confirmed by quotation.
START WITH THE WORKLOAD
The right fit
starts with the details.
Production inference, model development, and workloads suited to Hopper-based acceleration.
Deployment approach
Server configurations selected around the required accelerator form factor.
What we assess with you
- PCIe or SXM system requirements
- GPU memory, interconnects, and workload fit
- Power, cooling, and support coverage
Memory, form factor, condition, warranty, and delivery are confirmed for the exact quoted system.
FROM REQUIREMENT TO RUNNING SYSTEM
A clear scope, from the start.
- 01
Match the accelerator and server platform to your workload.
- 02
Plan networking, storage, and the required software stack.
- 03
Install, configure, and validate the agreed inference workload.
THE SERVICES AROUND YOUR HARDWARE
More than the compute.
Supply & install
Coordinate hardware supply, delivery, rack or workstation installation, networking, and power and cooling prerequisites.
Configure local inference
Set up supported drivers, CUDA, containers, and serving engines such as vLLM, Ollama, or NVIDIA NIM where suitable.
Validate & support
Check the agreed workload, access controls, monitoring, and recovery procedures. Hand over documentation and scope ongoing support.
From ambition to action
Let’s size the possibilities.
Share your models, expected usage, budget, location, and target deployment window. We’ll confirm the right configuration and sourcing options.