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:

pageResource 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 HGX

Hopper

80 GB

8

H100_NVLINK_80GB

H100 PCIe

Hopper

80 GB

8

H100_PCIE

A100 HGX

Ampere

80 GB

8

A100_NVLINK_80GB

A100 HGX

Ampere

40 GB

8

A100_NVLINK

A100 PCIe

Ampere

40 GB

8

A100_PCIE_40GB

A100 PCIe

Ampere

80 GB

8

A100_PCIE_80GB

A40

Ampere

48 GB

8

A40

RTX A6000

Ampere

48 GB

8

RTX_A6000

RTX A5000

Ampere

24 GB

8

RTX_A5000

RTX A4000

Ampere

16 GB

7

RTX_A4000

Tesla V100 NVLINK

Volta

16 GB

8

Tesla_V100_NVLINK

RTX 5000

Turing

16 GB

4

Quadro_RTX_5000

RTX 4000

Turing

8 GB

7

Quadro_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 v3

4 GB

70

intel-xeon-v3

Intel Xeon v4

4 GB

60

intel-xeon-v4

Intel Xeon Ice Lake

4 GB

94

intel-xeon-icelake

Intel Xeon Scalable

6 GB

94

intel-xeon-scalable

AMD Epyc Milan

4 GB

46

amd-epyc-milan

AMD Epyc Rome

4 GB

46

amd-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.

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