head to head · open source

llama.cpp vs taipy

llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. taipy has 19,453 stars, 1,999 forks, 225 open issues and last shipped 3 months ago. llama.cpp leads on adoption by 585% (133,181 vs 19,453 stars). llama.cpp is written in C++ under MIT; taipy is written in Python under Apache-2.0. llama.cpp has attracted 19% 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 ★ 133K taipy ★ 19K category AI & Machine Learning

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Side by side

	llama.cpp	taipy
GitHub stars	★ 133K	★ 19K
License	MIT	Apache-2.0
Written in	C++	Python
Last push	2026-11-02	2026-08-10
Forks	⑂ 25K	⑂ 2.0K
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 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 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 taipy

Build Python Data & AI web applications From simple pilots to production ready web applications in no time. No more compromises on performance, customization, and scalability. Go beyond existing libraries Table of Contents Taipy? What for? Taipy and its ecosystem Quickstart Documentation and resources Contributing Code of Conduct License ⭐ What for? Taipy is designed for data scientists and machine learning engineers to create data & AI driven web applications. ⭐️ Enables building production ready web applications. ⭐️ No need to learn new languages; only Python is needed. ⭐️ Focus on data and AI algorithms…

read the full taipy overview →

More in AI & Machine Learning

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Frequently asked questions

Is llama.cpp or taipy more popular?

llama.cpp has 133,181 GitHub stars and taipy has 19,453. 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 (133,181 stars) or its MIT licence terms. Choose taipy if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.