head to head · open source

llama.cpp vs embedJs

llama.cpp has 128,619 GitHub stars, 23,351 forks, 2,464 open issues and last shipped yesterday. embedJs has 602 stars, 76 forks, 18 open issues and last shipped 3 months ago. llama.cpp leads on adoption by 21,265% (128,619 vs 602 stars). llama.cpp is written in C++ under MIT; embedJs is written in TypeScript under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, embedJs 13%. 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 embedJs ★ 602 category AI & Machine Learning

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Side by side

	llama.cpp	embedJs
GitHub stars	★ 129K	★ 602
License	MIT	Apache-2.0
Written in	C++	TypeScript
Last push	2026-09-18	2026-06-26
Forks	⑂ 23K	⑂ 76
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 embedJs if

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

full embedJs 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 embedJs

EmbedJs is an Apache 2.0, TypeScript framework for Node.js that personalizes LLM responses by chunking your own data, generating embeddings, and storing them in a vector database for retrieval.

read the full embedJs overview →

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Frequently asked questions

Is llama.cpp or embedJs more popular?

llama.cpp has 128,619 GitHub stars and embedJs has 602. llama.cpp has the larger community by that measure.

Are llama.cpp and embedJs free?

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

What is the difference between llama.cpp and embedJs?

llama.cpp is written in C++ and embedJs in TypeScript. 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 embedJs?

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