llama.cpp vs Ollama

A side-by-side comparison to help you choose the right tool.

llama.cpp scores higher overall (90/100)

But the best choice depends on your specific needs. Compare below.

Pricing
Open-source project; no license fee for the runtime itself.
Free plan
Yes
Best for
Developers and hobbyists running models locally, Privacy-conscious users who want offline inference, Teams prototyping on laptops or edge devices
Platforms
mac, windows, linux, api
API
Yes
Languages
en
Pricing
Open-source project; free to use locally with your own hardware.
Free plan
Yes
Best for
Developers who want quick local model setup, Teams prototyping private/local AI workflows, Users who value a straightforward local API
Platforms
mac, windows, linux, api
API
Yes
Languages
en

Choose llama.cpp if:

  • You are Developers and hobbyists running models locally
  • You are Privacy-conscious users who want offline inference
  • You are Teams prototyping on laptops or edge devices
  • You want to start free
Read llama.cpp review →

Choose Ollama if:

  • You are Developers who want quick local model setup
  • You are Teams prototyping private/local AI workflows
  • You are Users who value a straightforward local API
  • You want to start free
Read Ollama review →

FAQ

What is the difference between llama.cpp and Ollama?
llama.cpp is the go-to open-source runtime for running many local llms on consumer hardware, especially via gguf models. Ollama is a simple local model runner and manager that makes downloading and serving local llms much easier than doing everything by hand.
Which is cheaper, llama.cpp or Ollama?
llama.cpp: Open-source project; no license fee for the runtime itself.. Ollama: Open-source project; free to use locally with your own hardware.. llama.cpp has a free plan. Ollama has a free plan.
Who is llama.cpp best for?
llama.cpp is best for Developers and hobbyists running models locally, Privacy-conscious users who want offline inference, Teams prototyping on laptops or edge devices.
Who is Ollama best for?
Ollama is best for Developers who want quick local model setup, Teams prototyping private/local AI workflows, Users who value a straightforward local API.