# Ollama vs llama.cpp vs vLLM: which local LLM runtime? | SelfHostAI

Source: https://ai.andreiturcea.com/ollama-vs-llama-cpp-vs-vllm.html
Last updated: 2026-10-15


**Short answer:** Use Ollama for the easiest local setup, llama.cpp for CPU, edge devices and fine control, and vLLM for high-throughput GPU serving to many users.

Last updated: 15 October 2026 · No tax figures on this site, so no GOV.UK check applies; tool details come from each project's public GitHub repository · [Markdown version](https://ai.andreiturcea.com/ollama-vs-llama-cpp-vs-vllm.html.md)

|  | [Ollama](https://ai.andreiturcea.com/tool-ollama.html) | [llama.cpp](https://ai.andreiturcea.com/tool-llama.cpp.html) | [vLLM](https://ai.andreiturcea.com/tool-vllm.html) |
|---|---|---|---|
| Best for | Easiest local setup | CPU, edge devices, full control | High-throughput GPU serving |
| Hardware | CPU or GPU | CPU or GPU | GPU |
| Licence | MIT | MIT | Apache-2.0 |
| Repo | [ollama/ollama](https://github.com/ollama/ollama) | [ggml-org/llama.cpp](https://github.com/ggml-org/llama.cpp) | [vllm-project/vllm](https://github.com/vllm-project/vllm) |

Rule of thumb: start with Ollama, drop to llama.cpp when you need fine control or very low resources, and move to vLLM when many users hit one GPU server. [LocalAI](https://ai.andreiturcea.com/tool-localai.html) is another OpenAI-compatible option. Add a UI from the [ChatGPT alternatives](https://ai.andreiturcea.com/best-self-hosted-chatgpt-alternatives.html) list.

## Frequently asked questions

### Should I use Ollama or llama.cpp?

Ollama is easier: one command to pull and run models, with an API. llama.cpp is the lower-level C/C++ engine, which gives more control and runs well on CPU.

### When should I use vLLM?

When you serve many concurrent requests on a GPU. vLLM is built for high-throughput serving rather than single-user desktop use.

### Do they offer an OpenAI-compatible API?

All three can expose an HTTP API that many OpenAI-compatible clients can use. Check each project's docs for the exact endpoints.