head to head · open source

llama.cpp vs arcadedb

llama.cpp has 128,619 GitHub stars, 23,351 forks, 2,464 open issues and last shipped today. arcadedb has 1,156 stars, 143 forks, 167 open issues and last shipped today. llama.cpp leads on adoption by 11,026% (128,619 vs 1,156 stars). llama.cpp is written in C++ under MIT; arcadedb is written in Java under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, arcadedb 12%. arcadedb 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 arcadedb ★ 1.2K category AI & Machine Learning

← all 8884 open source comparisons

Side by side

	llama.cpp	arcadedb
GitHub stars	★ 129K	★ 1.2K
License	MIT	Apache-2.0
Written in	C++	Java
Last push	2026-09-18	2026-09-18
Forks	⑂ 23K	⑂ 143
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 arcadedb if

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

full arcadedb 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 arcadedb

Multi Model DBMS Built for Extreme Performance ArcadeDB is a Multi Model DBMS created by Luca Garulli, the same founder of OrientDB, after SAP's acquisition. Written from scratch with a brand new engine made of Alien Technology, ArcadeDB is able to crunch millions of records per second on common hardware with minimal resource usage. ArcadeDB reuses OrientDB's SQL engine (heavily modified) and some utility classes. It's written in LLJ: Low Level Java still Java21+ but only using low level APIs to leverage advanced mechanical sympathy techniques and reduce Garbage Collector pressure. Highly optimized for extreme pe…

read the full arcadedb 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 PageIndex llama.cpp vs Langfuse llama.cpp vs cognee llama.cpp vs taipy llama.cpp vs dagster llama.cpp vs zvec llama.cpp vs langchain4j

Frequently asked questions

Is llama.cpp or arcadedb more popular?

llama.cpp has 128,619 GitHub stars and arcadedb has 1,156. llama.cpp has the larger community by that measure.

Are llama.cpp and arcadedb free?

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

What is the difference between llama.cpp and arcadedb?

llama.cpp is written in C++ and arcadedb in Java. 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 arcadedb?

Choose llama.cpp if you want the larger community (128,619 stars) or its MIT licence terms. Choose arcadedb if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.