head to head · open source
llama.cpp vs VectorDBBench
llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. VectorDBBench has 1,199 stars, 450 forks, 184 open issues and last shipped 5 days ago. llama.cpp leads on adoption by 11,008% (133,181 vs 1,199 stars). llama.cpp is written in C++ under MIT; VectorDBBench is written in Python under MIT. llama.cpp has attracted 19% as many forks as stars, VectorDBBench 38%. 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.
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Side by side
| llama.cpp | VectorDBBench | |
|---|---|---|
| GitHub stars | ★ 133K | ★ 1.2K |
| License | MIT | MIT |
| Written in | C++ | Python |
| Last push | 2026-11-02 | 2026-10-29 |
| Forks | ⑂ 25K | ⑂ 450 |
| 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
pick VectorDBBench if
- You want the VectorDBBench feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and VectorDBBench fits your workflow better
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 VectorDBBench
VectorDBBench(VDBBench): A Benchmark Tool for VectorDB What is VDBBench VDBBench is not just an offering of benchmark results for mainstream vector databases and cloud services, it's your go to tool for the ultimate performance and cost effectiveness comparison. Designed with ease of use in mind, VDBBench is devised to help users, even non professionals, reproduce results or test new systems, making the hunt for the optimal choice amongst a plethora of cloud services and open source vector databases a breeze. Understanding the importance of user experience, we provide an intuitive visual interface. This not only…
read the full VectorDBBench overview →
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Frequently asked questions
Is llama.cpp or VectorDBBench more popular?
llama.cpp has 133,181 GitHub stars and VectorDBBench has 1,199. llama.cpp has the larger community by that measure.
Are llama.cpp and VectorDBBench free?
Both are open source. llama.cpp is licensed under MIT and VectorDBBench under MIT. Neither carries a licence fee.
What is the difference between llama.cpp and VectorDBBench?
llama.cpp is written in C++ and VectorDBBench 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 VectorDBBench?
Choose llama.cpp if you want the larger community (133,181 stars) or its MIT licence terms. Choose VectorDBBench if its feature set, stack or MIT licence fits better. Both are self-hostable.