# Build and run vLLM on Arm servers

## In this learning path

- [Introduction](https://learn.arm.com/learning-paths/servers-and-cloud-computing/vllm/)
- [Build a vLLM from source code on Arm Linux](https://learn.arm.com/learning-paths/servers-and-cloud-computing/vllm/vllm-setup/)
- [Run batch inference using vLLM](https://learn.arm.com/learning-paths/servers-and-cloud-computing/vllm/vllm-run/)
- [Run an OpenAI-compatible vLLM server](https://learn.arm.com/learning-paths/servers-and-cloud-computing/vllm/vllm-server/)
- [Next Steps](https://learn.arm.com/learning-paths/servers-and-cloud-computing/vllm/_next-steps/)

## About this Learning Path

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| Skill level: | Introductory |
| Reading time: | 45 min |
| Last updated: | 09 Sep 2026 |

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| Author: | Jason Andrews , Arm<br>[GitHub](https://github.com/jasonrandrews)<br>[LinkedIn](https://linkedin.com/in/jason-andrews-7b05a8) |
| Arm IP: | [Neoverse](https://support.arm.com/?tab=compute-ip&Product%20Type=Infrastructure%20Processors) |
| Tags: | [ML](https://learn.arm.com/tag/ml) [AWS Graviton](https://learn.arm.com/tag/aws-graviton) [Microsoft Azure Cobalt](https://learn.arm.com/tag/microsoft-azure-cobalt) [Google Axion](https://learn.arm.com/tag/google-axion) [Oracle Cloud Infrastructure (OCI) Ampere Compute](https://learn.arm.com/tag/oracle-cloud-infrastructure-oci-ampere-compute) [Linux](https://learn.arm.com/tag/linux) [vLLM](https://learn.arm.com/tag/vllm) [LLM](https://learn.arm.com/tag/llm) [Generative AI](https://learn.arm.com/tag/generative-ai) [Python](https://learn.arm.com/tag/python) [Hugging Face](https://learn.arm.com/tag/hugging-face) |

### Who is this for?
This is an introductory topic for software developers and AI engineers interested in learning how to use the vLLM library on Arm servers.

### What will you learn?
After completing this Learning Path, you'll be able to perform the following tasks:
- Build vLLM from source on an Arm server.
- Use a Qwen LLM from Hugging Face.
- Run local batch inference using vLLM.
- Create and interact with an OpenAI-compatible server provided by vLLM on your Arm server.

### Prerequisites
Before starting, you'll need the following prerequisites:
- An [Arm-based Linux instance](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/) from a cloud service provider, or a local Arm Linux computer running Ubuntu 24.04 with at least 8 CPUs, 16 GB RAM, and 50 GB of disk storage.
- A system that includes support for BFloat16.