head to head · open source

llama.cpp vs cognee

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. cognee has 30,780 stars, 3,050 forks, 495 open issues and last shipped yesterday. llama.cpp leads on adoption by 318% (128,581 vs 30,780 stars). llama.cpp is written in C++ under MIT; cognee is written in Python under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, cognee 10%. cognee 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 cognee ★ 31K category AI & Machine Learning

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Side by side

	llama.cpp	cognee
GitHub stars	★ 129K	★ 31K
License	MIT	Apache-2.0
Written in	C++	Python
Last push	2026-09-17	2026-09-17
Forks	⑂ 23K	⑂ 3.0K
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 cognee if

You want the cognee 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 cognee fits your workflow better

full cognee 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 cognee

Cognee is an open source AI memory platform for agents, released under the Apache 2.0 license and written in Python. It ingests data in any format and builds a self hosted knowledge graph that agents query to recall, connect, and act with full context across sessions. The project lives in the Python ecosystem, installs through standard package managers, and sits in the AI and machine learning infrastructure category alongside graph databases and context engineering tooling. A companion research paper, "Optimizing the Interface Between Knowledge Graphs and LLMs for Complex Reasoning" by Markovic et al., 2025, docu…

read the full cognee overview →

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Frequently asked questions

Is llama.cpp or cognee more popular?

llama.cpp has 128,581 GitHub stars and cognee has 30,780. llama.cpp has the larger community by that measure.

Are llama.cpp and cognee free?

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

What is the difference between llama.cpp and cognee?

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

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