Use GPU MIG Partitioning

The Multi-Instance GPU (MIG) feature allows you to partition a physical GPU into multiple isolated instances, each with dedicated memory and compute resources.

MIG is useful when a full GPU would be too large for a single workload. By splitting one physical GPU into multiple GPU instances, you can run multiple smaller workloads on the same SKS node while giving each workload dedicated GPU memory and compute resources. This can improve GPU utilization for some workload types (e.g. AI inference).

Prerequisites

A GPU instance with a MIG-capable GPU. On Exoscale, the following GPU types support MIG:
- GPU A30
- GPU RTX Pro 6000

MIG helps improve utilization of the GPU resources you provision, but it does not change the billing unit and is only available on MIG-capable GPUs.

Enable MIG on SKS standard NodePools

Portal

You can enable one of the supported MIG profiles for your GPU type when you create or update a nodepool:

For new nodepools: navigate to SKS > your_cluster > Add Nodepool. Select a MIG-capable GPU instance type, then choose the desired MIG profile from the dropdown.
For existing nodepools: navigate to SKS > your_cluster > your_nodepool > Update Nodepool. Select the desired MIG profile from the dropdown.

Warning

To make your existing nodepool pick up the newly enabled MIG profile, you have to cycle your nodes.

CLI

The Exoscale CLI (starting from version 1.96.0) lets you enable a MIG profile on standard SKS nodepools. You only pass the profile name (e.g. 4g.24gb). The GPU family (a30.24gb or rtxpro6000.96gb) is automatically defined from the nodepool instance type.

Create a cluster with a default nodepool that has MIG enabled:

exo compute sks create my-cluster \
  --zone ch-gva-2 \
  --nodepool-name gpu-pool \
  --nodepool-size 1 \
  --nodepool-instance-type gpua30.large \
  --nodepool-nvidia-mig-profile 4g.24gb

Add a MIG-enabled nodepool to an existing cluster:

exo compute sks nodepool add my-cluster gpu-pool \
  --instance-type gpurtx6000pro.medium \
  --size 1 \
  --nvidia-mig-profile 1g.24gb

Update the MIG profile on an existing nodepool.

exo compute sks nodepool update my-cluster gpu-pool \
  --nvidia-mig-profile 2g.48gb

You can also pass an empty value to disable MIG.

Warning

Updating the MIG profile of an existing nodepool only affects newly provisioned nodes. To make current nodes pick up the new profile, you have to cycle your nodes.

Terraform provider

The Exoscale Terraform provider (starting from version 0.70.0) enables a MIG profile on a nodepool through the nvidia_mig_profile attribute of the exoscale_sks_nodepool resource. You only set the profile name (e.g. 4g.24gb). The GPU family (a30.24gb or rtxpro6000.96gb) is automatically deduced from the nodepool instance_type.

Create a MIG-enabled nodepool:

resource "exoscale_sks_nodepool" "gpu" {
  zone       = "ch-gva-2"
  cluster_id = exoscale_sks_cluster.my_cluster.id
  name       = "gpu-pool"

  instance_type      = "gpua30.large"
  size               = 1
  nvidia_mig_profile = "4g.24gb"
}

To change the profile, update nvidia_mig_profile and apply. To disable MIG, remove the attribute. The current profile is also exposed on the exoscale_sks_nodepool data source.

Warning

Updating the MIG profile of an existing nodepool only affects newly provisioned nodes. To make current nodes pick up the new profile, you have to cycle your nodes.

Enable MIG on Karpenter Nodepools

The SKS Node operating system is configured with TOML-formatted data.

Most critical parts of this data are set by our SKS product orchestrator. As a customer it’s possible to enrich this data with additional configuration.

In order to enable MIG, you can set specific configuration under both settings.kubelet-device-plugins.nvidia and settings.kubelet-device-plugins.nvidia.mig.profile entries on spec.userData of the Karpenter ExoscaleNodeClass resource.

For example if you want to select the “1g.24gb” profile on rtxpro6000 nodes, you can define:

apiVersion: karpenter.exoscale.com/v1
kind: ExoscaleNodeClass
metadata:
  name: nvidia-rtxpro6000-1g-24gb
spec:
  imageTemplateSelector:
    variant: nvidia
  diskSize: 100                                # Beware that GPU nodes enforce minimum disk size

  securityGroupSelectorTerms:
  - id: "5ea00f6e-1e92-456b-9381-2cb2c5937240" # Don't forget to attach proper security group

  userData: |
    [settings.kubelet-device-plugins.nvidia]
    device-partitioning-strategy = "mig"

    [settings.kubelet-device-plugins.nvidia.mig.profile]
    "rtxpro6000.96gb" = "1g.24gb"

On your referencing NodePool, nothing special except you need to select the proper instance type and reference the NodeClass:

apiVersion: karpenter.sh/v1
kind: NodePool
metadata:
  name: gpu-rtxpro6000-1g-24gb
spec:
  template:
    spec:
      nodeClassRef:
        group: karpenter.exoscale.com
        kind: ExoscaleNodeClass
        name: nvidia-rtxpro6000-1g-24gb
      requirements:
        - key: "node.kubernetes.io/instance-type"
          operator: In
          values:
            - "gpurtx6000pro.small"
            - "gpurtx6000pro.medium"
            - "gpurtx6000pro.large"
      taints:
        - key: "nvidia.com/gpu"
          value: "true"
          effect: "NoSchedule"
      expireAfter: 720h

  # [...]

  weight: 10

If a Pod requesting nvidia.com/gpu stays pending because of a lack of GPU, Karpenter will trigger the creation of a new GPU node with those characteristics:

apiVersion: v1
kind: Node
# [...]
spec:
# [...]
  taints:
  - effect: NoSchedule
    key: nvidia.com/gpu
    value: "true"
status:
# [...]
  allocatable:
    cpu: 35700m
    ephemeral-storage: "89785012888"
    hugepages-1Gi: "0"
    hugepages-2Mi: "0"
    memory: 123120044Ki
    nvidia.com/gpu: "4"
    pods: "110"
  capacity:
    cpu: "36"
    ephemeral-storage: 102083312Ki
    hugepages-1Gi: "0"
    hugepages-2Mi: "0"
    memory: 123632044Ki
    nvidia.com/gpu: "4"
    pods: "110"
# [...]

Supported MIG profiles

A30 MIG profiles

The a30.24gb device name comes with the available MIG profiles below:

MIG profile	# partitions
`1g.6gb`	4
`1g.6gb+me`	1
`2g.12gb`	2
`2g.12gb+me`	2
`4g.24gb`	1

Source: https://docs.nvidia.com/datacenter/tesla/mig-user-guide/latest/supported-mig-profiles.html#a30-mig-profiles

RTX6000PRO MIG profiles

The rtxpro6000.96gb device name comes with the available MIG profiles below:

MIG profile	# partitions
`1g.24gb`	4
`1g.24gb+me`	1
`1g.24gb+gfx`	4
`1g.24gb+me.all`	1
`1g.24gb-me`	4
`2g.48gb`	2
`2g.48gb+gfx`	2
`2g.48gb+me.all`	1
`2g.48gb-me`	2
`4g.96gb`	1
`4g.96gb+gfx`	1

Source: https://docs.nvidia.com/datacenter/tesla/mig-user-guide/latest/supported-mig-profiles.html#rtx-pro-6000-blackwell-mig-profiles

Profile References

The profile suffix indicates whether additional GPU capabilities are assigned to the MIG instance or not.

+me profiles: Include at least one media engine (NVDEC, NVENC, NVJPG, or OFA).
+gfx: Adds support for graphics APIs (new in GB20X).
+me.all: Allocates all available media engines to this instance (does not include graphics support).
-me: Excludes all media engines for pure compute workloads. Source: https://docs.nvidia.com/datacenter/tesla/mig-user-guide/latest/supported-mig-profiles.html

Limitations

Exoscale currently supports the single MIG strategy, i.e., all GPUs within a node are partitioned with the same profile. The mixed strategy (different profiles on the same GPU) is currently unsupported. For more details on MIG strategies, see the NVIDIA MIG configuration documentation.

References

Use GPU MIG Partitioning (on compute instance).
Multi-Instance GPU (MIG) allows you to partition a physical GPU into multiple isolated instances, each with dedicated memory and compute resources. This is particularly useful when you need to run multiple workloads that don’t require a full GPU.
Multi-Instance GPU (MIG) profiles

Last updated on July 17, 2026