Memory per GPU
Larger models and longer sequences need more HBM. H100 PCIe has 80 GB; H200 SXM has 141 GB. Check the full server configuration before comparing totals.
Explore H200GPU hardware for training
Plan the build, then check current supply and terms.
01 / Scope the workload
Start with the training job
Model size, training method, dataset, and deadline determine the GPU memory and interconnect you need. A single server and a multi-node cluster have very different network and facility requirements.
Send us these details
- Model and training method, such as full training or fine-tuning
- Target GPU family and count, if already chosen
- One server or multiple nodes
- Delivery location, target date, and facility power or cooling limits
An incomplete spec is fine. We can narrow it down with you.
02 / Compare the hardware
Where the GPU choice changes
GPU interconnect
Full training across GPUs depends on communication as well as compute. Ask whether a quoted server uses PCIe, NVLink/NVSwitch, or a platform-specific fabric.
Explore MI300XFacility fit
Power, cooling, rack space, and network links can rule out a build before price does. Confirm these with the exact server model and site.
Plan a rack03 / Get a written quote
Know the exact build before you commit
We check the requested configuration against current supply. The quote should identify the server model, GPU count and form factor, price, delivery estimate, and warranty terms. Integration or installation belongs in the quote only if it can be provided for that build.
Request a quote