head to head · open source

llama.cpp vs PageIndex

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. PageIndex has 35,678 stars, 3,148 forks, 103 open issues and last shipped yesterday. llama.cpp leads on adoption by 260% (128,581 vs 35,678 stars). llama.cpp is written in C++ under MIT; PageIndex is written in Python under MIT. llama.cpp has attracted 18% as many forks as stars, PageIndex 9%. 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 PageIndex ★ 36K category AI & Machine Learning

← all 8884 open source comparisons

Side by side

	llama.cpp	PageIndex
GitHub stars	★ 129K	★ 36K
License	MIT	MIT
Written in	C++	Python
Last push	2026-09-17	2026-09-17
Forks	⑂ 23K	⑂ 3.1K
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 PageIndex if

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

full PageIndex 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 PageIndex

PageIndex is a vectorless, reasoning based retrieval augmented generation engine written in Python and released under the MIT license. It lives in the AI and machine learning infrastructure ecosystem, with topics spanning RAG, information retrieval, LLM reasoning, context engineering, and agentic AI. Instead of building a vector index, PageIndex generates a hierarchical tree index for each document and then lets a large language model reason its way through that tree, in the same way a human expert turns to the right section of a long report. The project ships as a Python SDK, a hosted cloud service, and a docume…

read the full PageIndex overview →

More in AI & Machine Learning

Related comparisons

More Machine Learning Infrastructure projects

Compare either of these against the rest of the Machine Learning Infrastructure field.

llama.cpp vs Ollama llama.cpp vs vllm llama.cpp vs GPT4All llama.cpp vs llama_index llama.cpp vs LocalAI llama.cpp vs Langfuse llama.cpp vs cognee llama.cpp vs taipy llama.cpp vs dagster llama.cpp vs zvec llama.cpp vs langchain4j llama.cpp vs txtai

Frequently asked questions

Is llama.cpp or PageIndex more popular?

llama.cpp has 128,581 GitHub stars and PageIndex has 35,678. llama.cpp has the larger community by that measure.

Are llama.cpp and PageIndex free?

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

What is the difference between llama.cpp and PageIndex?

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

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