CoreWeave API
CoreWeave is a Kubernetes-native cloud GPU platform purpose-built for ML workloads, offering direct Kubernetes API access to NVIDIA H100, A100, and A40 GPU clusters with high-bandwidth InfiniBand networking for large-scale training and inference.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Kubernetes RBAC provides fine-grained access control with namespace and resource-level scoping. SOC 2 Type II and ISO 27001 certified. Dedicated tenant namespaces with network policy isolation. Enterprise-grade physical security in owned datacenters.
⚡ Reliability
Best When
You are running large-scale ML infrastructure requiring Kubernetes orchestration, InfiniBand networking, and enterprise-grade GPU availability with dedicated capacity.
Avoid When
You need simple on-demand VM access without Kubernetes expertise or are prototyping small workloads that don't justify enterprise contract overhead.
Use Cases
- • Deploy large-scale distributed training jobs using Kubernetes Jobs and PyTorchJob CRDs across multi-node H100 clusters with InfiniBand interconnects
- • Run managed inference endpoints by deploying containers as Kubernetes Deployments with GPU resource requests and CoreWeave's networking layer
- • Use the Kubernetes API to autoscale inference pods based on request queue depth via KEDA or HPA, matching capacity to traffic
- • Mount high-throughput Weka or Vast Data filesystem volumes via PersistentVolumeClaims for fast model loading and checkpoint writing
- • Automate multi-tenant ML platform provisioning by managing Kubernetes namespaces, resource quotas, and GPU node pools via API
Not For
- • Teams without Kubernetes expertise who need a simple VM-based or serverless GPU experience
- • Small-scale experiments or single-researcher workloads where the Kubernetes overhead is disproportionate to the workload
- • Organizations needing a public cloud marketplace with self-service signup and immediate access without enterprise sales engagement
Interface
Authentication
Kubernetes RBAC via kubeconfig and service accounts. API tokens scoped to namespaces and resource types via standard Kubernetes ClusterRole/Role bindings. CoreWeave provides a kubeconfig file per tenant.
Pricing
Enterprise agreements available with committed spend for discounts. Spot-equivalent 'preemptible' instances available at lower cost. Billing via monthly invoice for enterprise customers.
Agent Metadata
Known Gotchas
- ⚠ Access requires enterprise onboarding and kubeconfig provisioning — there is no self-service API key; agents cannot be provisioned without human-in-the-loop setup
- ⚠ GPU node availability for large pod requests (e.g., 8x H100) may require scheduling delays — agents must implement watch loops on pod status rather than assuming immediate scheduling
- ⚠ Kubernetes watch connections time out after ~5 minutes and must be re-established; agents using watch for event-driven workflows must handle reconnect logic
- ⚠ Container images must be pulled from a registry — large model images (100GB+) have significant pull latency; agents should use pre-cached images or PVC-mounted models
- ⚠ Namespace-level resource quotas can silently prevent pod scheduling; agents must check quota consumption before submitting jobs to avoid misleading 'Pending' state
Alternatives
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Scores are editorial opinions as of 2026-03-06.