head to head · open source

llama.cpp vs taipy

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. taipy has 19,436 stars, 1,993 forks, 225 open issues and last shipped 1 months ago. llama.cpp leads on adoption by 562% (128,581 vs 19,436 stars). llama.cpp is written in C++ under MIT; taipy is written in Python under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, taipy 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 ★ 129K taipy ★ 19K category AI & Machine Learning

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Side by side

	llama.cpp	taipy
GitHub stars	★ 129K	★ 19K
License	MIT	Apache-2.0
Written in	C++	Python
Last push	2026-09-17	2026-08-10
Forks	⑂ 23K	⑂ 2.0K
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 taipy if

You want the taipy 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 taipy fits your workflow better

full taipy 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 taipy

Taipy is an open source Python library and ecosystem for building data and AI driven web applications. It is designed for data scientists and machine learning engineers who want to turn data and AI algorithms into production ready web applications, and it lives in the Python ecosystem under the Apache 2.0 license. The project is maintained by Avaiga Private Limited and has been developed over roughly five years, with the repository showing 19,435 stars, 1,993 forks, and 225 open issues at the time of writing.

read the full taipy overview →

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Frequently asked questions

Is llama.cpp or taipy more popular?

llama.cpp has 128,581 GitHub stars and taipy has 19,436. llama.cpp has the larger community by that measure.

Are llama.cpp and taipy free?

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

What is the difference between llama.cpp and taipy?

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

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