CoreWeave
GPU cloud for AI workloads
0 case studies
General Infrastructure GPU cloud for AI workloads
Renting dedicated GPU clusters (A100, H100) for large-scale model training and inference workloads that need guaranteed capacity and high-bandwidth networking. It's favored by AI companies that need bare-metal GPU performance at lower cost than hyperscalers, with Kubernetes-native orchestration.
Sign up at coreweave.com and get approved for access (capacity is allocation-based). Use their Kubernetes-based platform with kubectl or their web console to provision GPU nodes. Set up your container images in their registry and deploy workloads as Kubernetes pods with GPU resource requests.
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