Choose a Proxmox VM CPU type based on the CPU features the guest needs and the processors on every node where the VM may run. Use host when migration compatibility is not a concern or cluster nodes have matching CPUs; for mixed or changing hardware, choose a generic model supported by all intended destinations. Set NUMA to describe a suitable guest topology and memory policy—not as a guaranteed speed boost.
What the CPU type changes
The CPU type determines which processor model and feature flags the guest operating system sees. With host, Proxmox exposes the host CPU’s features. A generic model instead presents a defined compatibility baseline, which can make the VM portable across hosts with different processors.
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That choice affects more than performance: guest-visible features can influence whether software runs, while the exposed feature set constrains which cluster nodes can start or receive the VM. Proxmox’s older Proxmox VE 6.4 guide, dated May 28, 2021, describes the tradeoff between a host CPU model and compatibility. For current model names and release-specific behavior, consult the documentation for the installed Proxmox VE version.
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Proxmox’s migration guidance says the CPU type should match the underlying hardware closely while still allowing live migration. In practice, the relevant compatibility floor is the least-capable node on which you intend to run the VM—not merely the newest server.
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| Cluster situation | CPU type to consider | Compatibility tradeoff |
|---|---|---|
| One node, or identical CPU models across the cluster | host |
Exposes the host CPU’s feature set. A VM may fail to migrate or start on a destination without those features. |
| Different CPU models, or likely hardware expansion | A generic x86-64-v<X> model supported by all intended targets |
Provides a compatibility baseline across hosts, but may not expose every feature available on the newest CPU. |
| Specific guest-visible feature selection is needed | A custom CPU model with selected flags | Allows controlled feature selection, but each requested feature must be compatible with the VM’s intended hosts and the installed Proxmox version’s restrictions. |
Proxmox recommends host when cluster nodes have the same CPU model, and generic x86-64-v<X> models when models differ or the cluster may gain different hardware. See the current Proxmox VE migration documentation for the release-specific guidance and available model choices.
When host is a good fit
Choose host when you want the guest to see the host CPU’s features and you do not need to move the VM to hardware with a different feature set. It is also an option when every intended destination has the same CPU model. Matching model names are a practical starting point, but migration compatibility still depends on the features available to the destination.
When to use a generic model
For a mixed-CPU cluster, choose a generic model that every intended destination supports. Check the oldest or least-featured target and the documentation for your installed Proxmox release before committing to a model. A portable baseline can reduce the guest-visible feature set compared with host; that is the compatibility tradeoff, not evidence that one model is universally faster.
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When a custom model makes sense
Custom CPU models let an administrator specify CPU flags. Use them when a defined feature set is required and the generic models do not express it. Proxmox documents details and restrictions that can vary by release; verify the flags against the installed version and every intended destination rather than assuming a flag will work throughout the cluster. See the custom CPU model documentation.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Configure NUMA for topology and memory placement
NUMA settings describe how the VM’s CPU and memory topology relates to host nodes and how memory should be placed. Proxmox’s qm command reference documents VM-level NUMA enablement and per-node topology fields, including CPUs, host nodes, memory, and policy. The documented policies include preferred, bind, and interleave.
These controls let you express a topology and placement policy; they do not determine the right mapping for every server or workload. The documented controls do not establish that enabling NUMA always improves VM performance, nor do they provide a universal CPU-socket-to-host-node recipe.
Information to check before changing NUMA
- Host topology: Identify the physical host’s NUMA nodes and how its CPUs and memory are arranged.
- VM allocation: Consider the VM’s vCPU count and memory allocation alongside the host topology.
- Guest behavior: Account for whether the guest operating system and its software can use the topology it is shown.
- Workload: Evaluate the actual application rather than assuming that a setting benefits all workloads.
If you do not know these details, avoid prescribing node counts, CPU assignments, or memory policies as universal defaults. Change topology or policy only with a clear goal, then compare workload behavior under the configurations you are evaluating.
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A practical decision process
- List the VM’s possible hosts. Include current cluster nodes where it may run and any planned destinations.
- Establish the CPU compatibility floor. Check the least-featured intended target and identify a generic model supported by all targets if CPU models differ.
- Choose the feature set. Use
hostwhen its host-specific feature exposure fits your migration constraints; use a generic model for broader compatibility; use a custom model only when you need deliberate flag selection. - Check the installed release documentation. Confirm model names, custom-model restrictions, and available
qmfields for your Proxmox VE version before applying settings. - Assess NUMA separately. Map the host topology, VM allocation, guest behavior, and workload before selecting guest topology or memory policy.
- Validate the outcome. Confirm the VM works on its intended nodes and, for NUMA tuning, compare the actual workload rather than relying on a general performance assumption.
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