head to head · open source

llama.cpp vs langtest

llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. langtest has 561 stars, 53 forks, 6 open issues and last shipped 2 months ago. llama.cpp leads on adoption by 23,640% (133,181 vs 561 stars). llama.cpp is written in C++ under MIT; langtest is written in Python under Apache-2.0. llama.cpp has attracted 19% as many forks as stars, langtest 9%. 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 langtest ★ 561 category AI & Machine Learning

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Side by side

	llama.cpp	langtest
GitHub stars	★ 133K	★ 561
License	MIT	Apache-2.0
Written in	C++	Python
Last push	2026-11-02	2026-08-28
Forks	⑂ 25K	⑂ 53
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 langtest if

You want the langtest feature set and don't need the biggest community
You prefer the Apache-2.0 license terms
Your stack matches Python
You evaluated both and langtest fits your workflow better

full langtest 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 langtest

LangTest: Deliver Safe & Effective Language Models Project's Website • Key Features • How To Use • Benchmark Datasets • Community Support • Contributing • Mission • License Project's Website Take a look at our official page for user documentation and examples: langtest.org Key Features Generate and execute more than 60 distinct types of tests only with 1 line of code Test all aspects of model quality: robustness, bias, representation, fairness and accuracy. Automatically augment training data based on test results (for select models) Support for popular NLP frameworks for NER, Translation and Text…

read the full langtest overview →

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Frequently asked questions

Is llama.cpp or langtest more popular?

llama.cpp has 133,181 GitHub stars and langtest has 561. llama.cpp has the larger community by that measure.

Are llama.cpp and langtest free?

Both are open source. llama.cpp is licensed under MIT and langtest under Apache-2.0. Neither carries a licence fee.

What is the difference between llama.cpp and langtest?

llama.cpp is written in C++ and langtest in Python. 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 langtest?

Choose llama.cpp if you want the larger community (133,181 stars) or its MIT licence terms. Choose langtest if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.