# Qwen2.5-0.5B on CPU

A 0.5B dense chat model served on CPUs alone, on a Civo CPU pool.

Source: /recipes/qwen2.5-0.5b-cpu/

<!-- vale write-good.Passive = NO -->
A 0.5B dense chat model served on CPUs alone, on a Civo `g4p.kube.medium`
pool: one `Standalone` engine, no cache, weights pulled straight from Hugging
Face. A CPU pool is the cheapest way to exercise a Modelplane deployment end
to end - no GPU to find, no driver to wait for - and a 0.5B model is small
enough that CPU inference answers in sensible time.

The class's provisioning block omits `accelerator`, which is what makes the
pool a CPU pool: the cluster composition builds it with a standard node image
and the `modelplane.ai/cpu` label and taint, and the serving stack installs
`dra-driver-cpu` - and no GPU machinery - because the class claims `dra.cpu`.
The claim pins the engine to its NUMA node's cpuset. The engine is vLLM's CPU
build, whose image serves the same OpenAI API as the CUDA one. The same class
without its provisioning block describes a bring-your-own CPU pool, on any
conformant cluster: label its nodes `modelplane.ai/pool=cpu-pool` and
`modelplane.ai/cpu=true` instead.

## Validated deployments

{{< validated-deployments >}}

## Platform

{{< manifests "recipes/qwen2.5-0.5b-cpu/inference-class.yaml" >}}

{{< manifests "recipes/qwen2.5-0.5b-cpu/inference-cluster.yaml" >}}

## Deployment

{{< manifests "recipes/qwen2.5-0.5b-cpu/model-deployment.yaml" >}}

{{< manifests "recipes/qwen2.5-0.5b-cpu/model-service.yaml" >}}
<!-- vale write-good.Passive = YES -->