head to head · open source

llama.cpp vs popmon

llama.cpp has 128,619 GitHub stars, 23,351 forks, 2,464 open issues and last shipped today. popmon has 511 stars, 35 forks, 12 open issues and last shipped 8 months ago. llama.cpp leads on adoption by 25,070% (128,619 vs 511 stars). llama.cpp is written in C++ under MIT; popmon is written in Python under MIT. llama.cpp has attracted 18% as many forks as stars, popmon 7%. 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 ★ 129K popmon ★ 511 category AI & Machine Learning

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Side by side

	llama.cpp	popmon
GitHub stars	★ 129K	★ 511
License	MIT	MIT
Written in	C++	Python
Last push	2026-09-18	2026-01-09
Forks	⑂ 23K	⑂ 35
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 popmon if

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

full popmon 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 popmon

=========================== Population Shift Monitoring =========================== popmon is a package that allows one to check the stability of a dataset. popmon works with both pandas and spark datasets . popmon creates histograms of features binned in time slices, and compares the stability of the profiles and distributions of those histograms using statistical tests , both over time and with respect to a reference. It works with numerical, ordinal, categorical features, and the histograms can be higher dimensional, e.g. it can also track correlations between any two features. popmon can automatically flag an…

read the full popmon overview →

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Frequently asked questions

Is llama.cpp or popmon more popular?

llama.cpp has 128,619 GitHub stars and popmon has 511. llama.cpp has the larger community by that measure.

Are llama.cpp and popmon free?

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

What is the difference between llama.cpp and popmon?

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

Choose llama.cpp if you want the larger community (128,619 stars) or its MIT licence terms. Choose popmon if its feature set, stack or MIT licence fits better. Both are self-hostable.