head to head · open source

llama.cpp vs next-plaid

llama.cpp has 128,619 GitHub stars, 23,351 forks, 2,464 open issues and last shipped yesterday. next-plaid has 546 stars, 60 forks, 29 open issues and last shipped 25 days ago. llama.cpp leads on adoption by 23,457% (128,619 vs 546 stars). llama.cpp is written in C++ under MIT; next-plaid is written in Rust under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, next-plaid 11%. 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 next-plaid ★ 546 category AI & Machine Learning

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Side by side

	llama.cpp	next-plaid
GitHub stars	★ 129K	★ 546
License	MIT	Apache-2.0
Written in	C++	Rust
Last push	2026-09-18	2026-08-25
Forks	⑂ 23K	⑂ 60
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 next-plaid if

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

full next-plaid 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 next-plaid

NextPlaid is a multi vector search engine written in Rust, and ColGREP is the semantic code search tool built on top of it for developers who work in the terminal and for the coding agents that run beside them.

read the full next-plaid overview →

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Frequently asked questions

Is llama.cpp or next-plaid more popular?

llama.cpp has 128,619 GitHub stars and next-plaid has 546. llama.cpp has the larger community by that measure.

Are llama.cpp and next-plaid free?

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

What is the difference between llama.cpp and next-plaid?

llama.cpp is written in C++ and next-plaid 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 next-plaid?

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