# GPU Cloud Evaluation Report

### Learn how the Rafay Platform delivers a GPU Cloud for enterprises and service providers

Most organizations have invested heavily in GPU infrastructure, but building a GPU cloud that teams can actually use is a different challenge. GPUs are expensive, scarce, and often underutilized, while developers and data scientists are blocked by manual provisioning, fragmented environments, and limited access. Without a self-service model, GPU infrastructure becomes a bottleneck instead of an accelerator.

This report explores how leading organizations deliver a self-service GPU cloud that transforms raw infrastructure into a scalable platform. By pooling resources, enabling on-demand access, and introducing multi-tenant governance, teams can dramatically improve GPU utilization, reduce costs, and give developers immediate access to the compute they need to build and ship AI applications faster.

### What you’ll learn:

- What defines a modern GPU cloud and why self-service access is critical
- How to improve GPU utilization and reduce wasted infrastructure spend
- What capabilities are required to deliver a scalable, multi-tenant GPU cloud platform

[View the report](https://cdn.prod.website-files.com/68d15699b1e46604cd1fe6a6/68d1569ab1e46604cd1ff1e6_PN-Rafay-GPU-Cloud-Eval-2024-v1.0-RC1%20(1).pdf)

## Rafay's Valued Partnerships: