head to head · open source

llama.cpp vs autoflow

llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. autoflow has 2,978 stars, 193 forks, 74 open issues and last shipped 11 days ago. llama.cpp leads on adoption by 4,372% (133,181 vs 2,978 stars). llama.cpp is written in C++ under MIT; autoflow is written in TypeScript under Apache-2.0. llama.cpp has attracted 19% as many forks as stars, autoflow 6%. 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 autoflow ★ 3.0K category AI & Machine Learning

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Side by side

	llama.cpp	autoflow
GitHub stars	★ 133K	★ 3.0K
License	MIT	Apache-2.0
Written in	C++	TypeScript
Last push	2026-11-02	2026-10-23
Forks	⑂ 25K	⑂ 193
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 autoflow if

You want the autoflow feature set and don't need the biggest community
You prefer the Apache-2.0 license terms
Your stack matches TypeScript
You evaluated both and autoflow fits your workflow better

full autoflow 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 autoflow

AutoFlow [!WARNING] Autoflow is still in the early stages of development. And we are actively working on it, the next move is to make it to a python package and make it a RAG solution e.g. pip install autoflow ai . If you have any questions or suggestions, please feel free to contact us on Discussion. Introduction AutoFlow is an open source graph rag (graphrag: knowledge graph rag) based knowledge base tool built on top of TiDB Vector and LlamaIndex and DSPy. Live Demo : Deployment Docs : Deployment Docs Features 1. Perplexity style Conversational Search page : Our platform features an advanced built in website…

read the full autoflow overview →

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Frequently asked questions

Is llama.cpp or autoflow more popular?

llama.cpp has 133,181 GitHub stars and autoflow has 2,978. llama.cpp has the larger community by that measure.

Are llama.cpp and autoflow free?

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

What is the difference between llama.cpp and autoflow?

llama.cpp is written in C++ and autoflow in TypeScript. 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 autoflow?

Choose llama.cpp if you want the larger community (133,181 stars) or its MIT licence terms. Choose autoflow if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.