head to head · open source

llama.cpp vs paradedb

llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. paradedb has 9,473 stars, 496 forks, 193 open issues and last shipped yesterday. llama.cpp leads on adoption by 1,306% (133,181 vs 9,473 stars). llama.cpp is written in C++ under MIT; paradedb is written in Rust under AGPL-3.0. llama.cpp has attracted 19% as many forks as stars, paradedb 5%. paradedb 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 paradedb ★ 9.5K category AI & Machine Learning

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Side by side

	llama.cpp	paradedb
GitHub stars	★ 133K	★ 9.5K
License	MIT	AGPL-3.0
Written in	C++	Rust
Last push	2026-11-02	2026-11-02
Forks	⑂ 25K	⑂ 496
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 paradedb if

You want the paradedb feature set and don't need the biggest community
You prefer the AGPL-3.0 license terms
Your stack matches Rust
You evaluated both and paradedb fits your workflow better

full paradedb 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 paradedb

Search without a second system. One Postgres for your application data, full text search, vector retrieval, and aggregations. Website • Docs • Community • Blog • Changelog Installation To install ParadeDB locally in a fresh Docker container and drop straight into a psql session: When you're ready to deploy, check out our hosting options. What is ParadeDB? ParadeDB upgrades Postgres with a custom index for fast full text and vector search, BM25 scoring, filtering, and aggregations. Your application data and search engine live in one database, with no second system to deploy and nothing to…

read the full paradedb overview →

More in AI & Machine Learning

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Frequently asked questions

Is llama.cpp or paradedb more popular?

llama.cpp has 133,181 GitHub stars and paradedb has 9,473. llama.cpp has the larger community by that measure.

Are llama.cpp and paradedb free?

Both are open source. llama.cpp is licensed under MIT and paradedb under AGPL-3.0. Neither carries a licence fee.

What is the difference between llama.cpp and paradedb?

llama.cpp is written in C++ and paradedb in Rust. 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 paradedb?

Choose llama.cpp if you want the larger community (133,181 stars) or its MIT licence terms. Choose paradedb if its feature set, stack or AGPL-3.0 licence fits better. Both are self-hostable.