head to head · open source

llama.cpp vs great_expectations

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. great_expectations has 11,797 stars, 1,850 forks, 42 open issues and last shipped yesterday. llama.cpp leads on adoption by 990% (128,581 vs 11,797 stars). llama.cpp is written in C++ under MIT; great_expectations is written in Python under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, great_expectations 16%. great_expectations 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 great_expectations ★ 12K category AI & Machine Learning

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Side by side

	llama.cpp	great_expectations
GitHub stars	★ 129K	★ 12K
License	MIT	Apache-2.0
Written in	C++	Python
Last push	2026-09-17	2026-09-17
Forks	⑂ 23K	⑂ 1.9K
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 great_expectations if

You want the great_expectations 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 great_expectations fits your workflow better

full great_expectations 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 great_expectations

Great Expectations, referred to in its own documentation as GX Core, is an open source Python library for validating and documenting the quality of data. It lives in the Python data ecosystem and is published under the Apache 2.0 license. The project has been in development for roughly nine years and carries about 11,794 stars with 1,848 forks, which places it among the longer running tools in the data quality space. Its central concept is the Expectation: an expressive, extensible unit test written against a dataset rather than against application code.

read the full great_expectations overview →

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Frequently asked questions

Is llama.cpp or great_expectations more popular?

llama.cpp has 128,581 GitHub stars and great_expectations has 11,797. llama.cpp has the larger community by that measure.

Are llama.cpp and great_expectations free?

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

What is the difference between llama.cpp and great_expectations?

llama.cpp is written in C++ and great_expectations 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 great_expectations?

Choose llama.cpp if you want the larger community (128,581 stars) or its MIT licence terms. Choose great_expectations if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.