Compare Pacific vs. Rafay

Pacific specializes in offering GPU computing rentals and modular AI infrastructure tailored for enterprises engaged in AI training, fine-tuning, and inference tasks. Their service catalog features on-demand dedicated NVIDIA GPU nodes, such as H100, H200, and B200 configurations, with the option for larger systems and reserved capacities upon request. The rentals include SSH access to bare-metal Linux hosts equipped with NVIDIA drivers and CUDA technology. For clients with longer-term or specific site requirements, Pacific provides reserved single-tenant clusters, managed on-premises installations, colocation solutions, and bridge capacity while permanent facilities are being established. Their factory-assembled modules integrate compute, networking, cooling, and power distribution, making them suitable for customer sites, colocation centers, or any other viable powered locations. The clientele comprises AI teams and infrastructure managers assessing their training or inference capabilities, along with organizations seeking enhanced control over their computing deployments. Additionally, Pacific's modular infrastructure can be quickly deployed, allowing for flexibility in scaling resources as AI projects evolve.

Rafay helps enterprises, neoclouds, telcos, sovereign AI clouds, and service providers transform GPU and CPU infrastructure into secure, self-service platforms for AI innovation, consumption, and monetization. The Rafay Platform sits between accelerated infrastructure and the teams or customers consuming it, helping organizations move from raw compute to production-ready AI platforms faster. With Rafay, platform teams can orchestrate, govern, and automate infrastructure across data centers, cloud, hybrid, and air-gapped or sovereign environments. Teams can deliver self-service access to GPU resources, Kubernetes clusters, virtual machines, SLURM environments, AI workbenches, inference services, and application catalogs while maintaining control through policies, access controls, quotas, audit trails, and usage visibility. Rafay supports multiple teams, tenants, customers, and business units on shared infrastructure. Secure multi-tenancy, cost visibility, chargeback, and lifecycle automation help maximize GPU utilization while giving developers and data scientists fast access to the environments they need. For neoclouds, GPU cloud providers, telcos, and service providers, Rafay helps turn infrastructure investments into differentiated services. Providers can package compute and AI capabilities into consumable SKUs, deliver self-service GPU and AI platforms, and monetize usage through consumption-based models. Rafay unifies orchestration, governance, consumption, and monetization so organizations can accelerate AI adoption and turn infrastructure into a launchpad for innovation.