head to head · open source
llama.cpp vs great_expectations
llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. great_expectations has 11,914 stars, 1,883 forks, 42 open issues and last shipped yesterday. llama.cpp leads on adoption by 1,018% (133,181 vs 11,914 stars). llama.cpp is written in C++ under MIT; great_expectations is written in Python under Apache-2.0. llama.cpp has attracted 19% as many forks as stars, great_expectations 16%. 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.
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Side by side
| llama.cpp | great_expectations | |
|---|---|---|
| GitHub stars | ★ 133K | ★ 12K |
| License | MIT | Apache-2.0 |
| Written in | C++ | Python |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 25K | ⑂ 1.9K |
| 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
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
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 great_expectations
About GX Core GX Core combines the collective wisdom of thousands of community members with a proven track record in data quality deployments worldwide, wrapped into a super simple package for data teams. Its powerful technical tools start with Expectations: expressive and extensible unit tests for your data. Expectations foster collaboration by giving teams a common language to express data quality tests in an intuitive way. You can automatically generate documentation for each set of validation results, making it easy for everyone to stay on the same page. This not only simplifies your data quality processes…
read the full great_expectations overview →
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Frequently asked questions
Is llama.cpp or great_expectations more popular?
llama.cpp has 133,181 GitHub stars and great_expectations has 11,914. 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 (133,181 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.