head to head · open source

llama.cpp vs LLPhant

llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. LLPhant has 1,722 stars, 179 forks, 36 open issues and last shipped yesterday. llama.cpp leads on adoption by 7,634% (133,181 vs 1,722 stars). llama.cpp is written in C++ under MIT; LLPhant is written in PHP under MIT. llama.cpp has attracted 19% as many forks as stars, LLPhant 10%. llama.cpp 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 ★ 133K LLPhant ★ 1.7K category AI & Machine Learning

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Side by side

	llama.cpp	LLPhant
GitHub stars	★ 133K	★ 1.7K
License	MIT	MIT
Written in	C++	PHP
Last push	2026-11-02	2026-11-02
Forks	⑂ 25K	⑂ 179
Self-hosting	Yes	Yes
Data ownership	Your server	Your server

pick llama.cpp if

You weight community size — 133K 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 LLPhant if

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

full LLPhant profile →

About llama.cpp

llama.cpp LLM inference in C/C++ ggml / ops / maintainer PRs%20sort%3Aupdated desc) / dev stats / lib llama API / llama server REST API Quick start A few options to get llama.cpp installed on your machine: Visit and follow the instructions Run with Docker see our Docker documentation Download pre built binaries from the releases page Build from source by cloning this repository check out our build guide Once installed: VLM session with llama cli Built in web UI against llama serve Description The main goal of llama.cpp is to enable LLM (and VLM) inference with minimal setup and state of the art performance on a…

read the full llama.cpp overview →

About LLPhant

LLPhant The PHP library for Gen AI and Vector Databases We designed this framework to be as simple as possible, while still providing you with the tools you need to build powerful apps. It is compatible with Symfony and Laravel. We are working to expand the support of different LLMs. Right now, we are supporting OpenAI, Anthropic, Mistral, Ollama, llmman, LM Studio, Atlas Cloud and services compatible with the OpenAI API such as LocalAI. Ollama that can be used to run LLM locally such as Llama 2. We want to thank few amazing projects that we use here or inspired us: the learnings from using LangChain and…

read the full LLPhant overview →

More in AI & Machine Learning

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Frequently asked questions

Is llama.cpp or LLPhant more popular?

llama.cpp has 133,181 GitHub stars and LLPhant has 1,722. llama.cpp has the larger community by that measure.

Are llama.cpp and LLPhant free?

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

What is the difference between llama.cpp and LLPhant?

llama.cpp is written in C++ and LLPhant in PHP. 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 LLPhant?

Choose llama.cpp if you want the larger community (133,181 stars) or its MIT licence terms. Choose LLPhant if its feature set, stack or MIT licence fits better. Both are self-hostable.