head to head · open source

llama.cpp vs zvec

llama.cpp has 128,880 GitHub stars, 23,468 forks, 2,464 open issues and last shipped today. zvec has 15,972 stars, 998 forks, 56 open issues and last shipped today. llama.cpp leads on adoption by 707% (128,880 vs 15,972 stars). llama.cpp is written in C++ under MIT; zvec is written in C++ under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, zvec 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 ★ 129K zvec ★ 16K category AI & Machine Learning

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Side by side

llama.cpp zvec
GitHub stars ★ 129K ★ 16K
License MIT Apache-2.0
Written in C++ C++
Last push 2026-09-20 2026-09-20
Forks ⑂ 23K ⑂ 998
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 zvec if

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

full zvec 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 zvec

Zvec is an open source, in process vector database written in C++ and licensed under Apache 2.0, built to embed directly into applications so that vector search, full text search, and hybrid retrieval run inside the developer's own process instead of behind a separate service.

read the full zvec overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 247K Ollama ★ 181K Dify ★ 157K Open WebUI ★ 153K langchain ★ 147K

Related comparisons

ollama vs llama-cpp openclaw vs ollama ollama vs vllm ollama vs odysseus ollama vs gpt4all ollama vs llama-index ollama vs localai open-webui vs gpt4all openclaw vs hermes-agent openclaw vs opencode openclaw vs n8n openclaw vs open-webui openclaw vs comfyui openclaw vs odysseus openclaw vs lobechat openclaw vs anythingllm openclaw vs dify openclaw vs multica openclaw vs langgraph n8n vs dify dify vs langflow dify vs open-webui dify vs langchain dify vs ponytail

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 faiss llama.cpp vs PageIndex llama.cpp vs Langfuse llama.cpp vs cognee llama.cpp vs taipy llama.cpp vs dagster llama.cpp vs langchain4j

Frequently asked questions

Is llama.cpp or zvec more popular?

llama.cpp has 128,880 GitHub stars and zvec has 15,972. llama.cpp has the larger community by that measure.

Are llama.cpp and zvec free?

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

What is the difference between llama.cpp and zvec?

llama.cpp is written in C++ and zvec in C++. 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 zvec?

Choose llama.cpp if you want the larger community (128,880 stars) or its MIT licence terms. Choose zvec if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.