Dedicated GPU Server
Cloud & Sovereign ComputePhysical GPU hardware reserved exclusively for a single customer, no shared tenancy, maximum performance, complete data isolation.
Eleveight AI's Dedicated Compute product reserves an entire B300 cluster exclusively for one customer: bare metal performance, full data isolation, no shared tenancy.
Overview
A dedicated GPU server hands one customer exclusive use of an entire physical machine, its compute, memory, storage, and accelerators alike. No other organization's workloads run alongside, and no other organization's data ever travels through the same processors. Where shared cloud divides a machine among many tenants, the dedicated model draws a hard boundary: one tenant, one set of hardware.
How it works
The provider allocates specific physical servers to a single customer for the duration of their reservation. Because nothing is shared, there is no contention for resources and no neighbor whose activity affects performance. In Eleveight AI's case this pairs with bare metal access, so the customer's software addresses the hardware directly, without a hypervisor between it and the silicon.
Why it matters
For regulated sectors, exclusivity is frequently not a preference but a requirement. Compliance regimes in finance, healthcare, and government often demand that sensitive data never physically coexists with another party's on the same machine. Dedicated hardware satisfies that plainly, while also delivering the steady, contention-free performance that production workloads with firm commitments need.
Use cases
- AI model training with strict data privacy requirements
- Government and defence AI workloads
- Healthcare AI under data residency regulations
- Financial services with strict compliance requirements