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Node Types

important

Due to high demand, A100 NVLINK (HGX) and H100 NVLINK (HGX) nodes are currently fully committed on client contracts, and are therefore not available for on-demand use. We recommend a conversation with the CoreWeave team to build a strategic plan catered to your needs to make use of available infrastructure and to plan for your future capacity requirements. Contact CoreWeave Sales to get started.

CoreWeave offers a "Standard Instance," which is useful for most workloads per GPU type offered on CoreWeave Cloud. These instances are a starting point, but can be configured entirely to suit your use case or compute needs.

You can view Standard Instance configurations on our website's pricing page.

For more information about à la carte pricing of compute components on CoreWeave Cloud, see Resource Based Pricing.

Component availability

The following table outlines the physical limitation of how many GPUs are available per instance when customizing your instances on CoreWeave Cloud.

ClassGenerationVRAMMax per InstanceLabel
H100 HGXHopper80 GB8H100_NVLINK_80GB
H100 PCIeHopper80 GB8H100_PCIE
A100 HGXAmpere80 GB8A100_NVLINK_80GB
A100 HGXAmpere40 GB8A100_NVLINK
A100 PCIeAmpere40 GB8A100_PCIE_40GB
A100 PCIeAmpere80 GB8A100_PCIE_80GB
A40Ampere48 GB8A40
RTX A6000Ampere48 GB8RTX_A6000
RTX A5000Ampere24 GB8RTX_A5000
RTX A4000Ampere16 GB7RTX_A4000
Tesla V100 NVLINKVolta16 GB8Tesla_V100_NVLINK
RTX 5000Turing16 GB4Quadro_RTX_5000
RTX 4000Turing8 GB7Quadro_RTX_4000
important

If a workload requests more peripheral compute resources (vCPU, RAM) than offered in a standard instance size, additional costs will incur.

CPU availability

CPU-only nodes are best suited for tasks such as control-plane services, databases, ingresses and CPU rendering.

CPU ModelMax RAM per vCPUMax vCPU per WorkloadLabel
Intel Xeon v34 GB70intel-xeon-v3
Intel Xeon v44 GB60intel-xeon-v4
Intel Xeon Ice Lake4 GB94intel-xeon-icelake
Intel Xeon Scalable6 GB94intel-xeon-scalable
AMD Epyc Milan4 GB46amd-epyc-milan
AMD Epyc Rome4 GB46amd-epyc-rome
note

Workloads without GPU requests are always scheduled on CPU nodes.

Requesting compute in Kubernetes

A combination of resource requests and node affinity is used to select the type and amount of compute for your workload. CoreWeave Cloud relies only on these native Kubernetes methods for resource allocation, allowing maximum flexibility. The label used to select the GPU type is gpu.nvidia.com/class. CPU type is selected using the label node.coreweave.cloud/cpu.

note

These labels are mutually exclusive - a specific CPU type cannot be explicitly selected for GPU nodes.

Example specs

spec:
containers:
- name: example
resources:
limits:
cpu: 15
memory: 97Gi
nvidia.com/gpu: 1

affinity:
nodeAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
nodeSelectorTerms:
- matchExpressions:
- key: gpu.nvidia.com/class
operator: In
values:
- A100_PCIE_80GB
note

Kubernetes allows resources to be scheduled with requests and limits. When only limits are specified, the requests are set to the same amount as the limit.