Size & source
Map your models, users, budget, and site requirements. Compare supplier configurations and confirm the exact bill of materials.
GPU accelerators / Hopper
NVIDIA H20.
Discuss H20-class inference requirements and supplier-confirmed configurations for your deployment.
Configuration, availability, and commercial terms confirmed by quotation.
START WITH THE WORKLOAD
The right fit
starts with the details.
Inference workloads where an H20 configuration is available and appropriate for the deployment region.
Deployment approach
Compatible server configurations, subject to supplier and destination eligibility.
What we assess with you
- Exact accelerator variant and server compatibility
- Model memory requirements and concurrency
- Destination eligibility and supply terms
Looking for H20e? Include the supplier’s exact H20e part number in your enquiry so we can confirm the designation, configuration, and supply eligibility before quoting.
FROM REQUIREMENT TO RUNNING SYSTEM
A clear scope, from the start.
- 01
Validate the requested part number and system bill of materials.
- 02
Check the intended model, context lengths, and target throughput.
- 03
Quote eligible supply, installation, and configuration separately.
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.