head to head · open source

llama.cpp vs qdrant-client

llama.cpp has 128,619 GitHub stars, 23,351 forks, 2,464 open issues and last shipped today. qdrant-client has 1,357 stars, 303 forks, 191 open issues and last shipped 2 days ago. llama.cpp leads on adoption by 9,378% (128,619 vs 1,357 stars). llama.cpp is written in C++ under MIT; qdrant-client is written in Python under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, qdrant-client 22%. 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 ★ 129K qdrant-client ★ 1.4K category AI & Machine Learning

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Side by side

	llama.cpp	qdrant-client
GitHub stars	★ 129K	★ 1.4K
License	MIT	Apache-2.0
Written in	C++	Python
Last push	2026-09-18	2026-09-16
Forks	⑂ 23K	⑂ 303
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 qdrant-client if

You want the qdrant-client 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 qdrant-client fits your workflow better

full qdrant-client 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 qdrant-client

Python Client library for the Qdrant vector search engine. Python Qdrant Client Client library and SDK for the Qdrant vector search engine. Library contains type definitions for all Qdrant API and allows to make both Sync and Async requests. Client allows calls for all Qdrant API methods directly. It also provides some additional helper methods for frequently required operations, e.g. initial collection uploading. See QuickStart for more details! Installation Features Type hints for all API methods Local mode use same API without running server REST and gRPC support Minimal dependencies Extensive Test Coverage Lo…

read the full qdrant-client overview →

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Frequently asked questions

Is llama.cpp or qdrant-client more popular?

llama.cpp has 128,619 GitHub stars and qdrant-client has 1,357. llama.cpp has the larger community by that measure.

Are llama.cpp and qdrant-client free?

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

What is the difference between llama.cpp and qdrant-client?

llama.cpp is written in C++ and qdrant-client 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 qdrant-client?

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