head to head · open source

llama.cpp vs LocalAI

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. LocalAI has 49,144 stars, 4,455 forks, 201 open issues and last shipped yesterday. llama.cpp leads on adoption by 162% (128,581 vs 49,144 stars). llama.cpp is written in C++ under MIT; LocalAI is written in Go under MIT. llama.cpp has attracted 18% as many forks as stars, LocalAI 9%. LocalAI was the more recently maintained of the two, and both are self-hostable with no licence fee.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

llama.cpp ★ 129K LocalAI ★ 49K category AI & Machine Learning

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Side by side

	llama.cpp	LocalAI
GitHub stars	★ 129K	★ 49K
License	MIT	MIT
Written in	C++	Go
Last push	2026-09-17	2026-09-17
Forks	⑂ 23K	⑂ 4.5K
Self-hosting	Yes	Yes
Data ownership	Your server	Your server

pick llama.cpp if

You weight community size — 129K stars and counting
You want the MIT license terms
Your stack matches C++
You value the larger contributor base for long-term maintenance

full llama.cpp profile →

pick LocalAI if

You want the LocalAI feature set and don't need the biggest community
You prefer the MIT license terms
Your stack matches Go
You evaluated both and LocalAI fits your workflow better

full LocalAI profile →

About llama.cpp

llama.cpp is a C/C++ library and set of command line tools for running large language models (LLMs) and vision language models (VLMs) locally. It enables inference without external dependencies, targeting diverse hardware including Apple Silicon, x86 CPUs, NVIDIA GPUs (via CUDA), AMD GPUs (via HIP), and other accelerators. The project lives in the ggml ecosystem, leveraging the ggml tensor computation library for low level operations and quantized model execution.

read the full llama.cpp overview →

About LocalAI

LocalAI is an open source AI runtime that enables running large language models (LLMs), vision, audio, image, and video models locally or on premises. It operates as a modular engine where each model type is backed by a dedicated, lightweight backend—such as llama.cpp, whisper.cpp, or stable diffusion—pulled only when needed. This composable architecture avoids bundling unnecessary dependencies, keeping the core minimal while supporting diverse modalities and hardware configurations.

read the full LocalAI overview →

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Frequently asked questions

Is llama.cpp or LocalAI more popular?

llama.cpp has 128,581 GitHub stars and LocalAI has 49,144. llama.cpp has the larger community by that measure.

Are llama.cpp and LocalAI free?

Both are open source. llama.cpp is licensed under MIT and LocalAI under MIT. Neither carries a licence fee.

What is the difference between llama.cpp and LocalAI?

llama.cpp is written in C++ and LocalAI in Go. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, llama.cpp or LocalAI?

Choose llama.cpp if you want the larger community (128,581 stars) or its MIT licence terms. Choose LocalAI if its feature set, stack or MIT licence fits better. Both are self-hostable.