head to head · open source

llama.cpp vs llama_index

llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. llama_index has 52,779 stars, 8,500 forks, 770 open issues and last shipped 8 days ago. llama.cpp leads on adoption by 152% (133,181 vs 52,779 stars). llama.cpp is written in C++ under MIT; llama_index is written in Python under MIT. llama.cpp has attracted 19% as many forks as stars, llama_index 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.

llama.cpp ★ 133K llama_index ★ 53K category AI & Machine Learning

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Side by side

	llama.cpp	llama_index
GitHub stars	★ 133K	★ 53K
License	MIT	MIT
Written in	C++	Python
Last push	2026-11-02	2026-10-26
Forks	⑂ 25K	⑂ 8.5K
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 llama_index if

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

full llama_index 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 llama_index

🗂️ LlamaIndex (OSS Framework) 🦙 [!NOTE] The current focus of LlamaIndex is to build the best AI powered engine for document parsing and extraction. LlamaParse is our enterprise platform for agentic OCR, parsing, extraction, indexing and more. LiteParse represents our efforts to build the best free, fast, cheap text parser in the market. ParseBench and ExtractBench represent our commitment towards open benchmarking for parsing and extraction. The company itself has undergone an evolution since when this OSS framework first launched 3 years ago in 2023. Since the early days, the framework has consisted of a…

read the full llama_index overview →

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Frequently asked questions

Is llama.cpp or llama_index more popular?

llama.cpp has 133,181 GitHub stars and llama_index has 52,779. llama.cpp has the larger community by that measure.

Are llama.cpp and llama_index free?

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

What is the difference between llama.cpp and llama_index?

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

Choose llama.cpp if you want the larger community (133,181 stars) or its MIT licence terms. Choose llama_index if its feature set, stack or MIT licence fits better. Both are self-hostable.