head to head · open source

llama.cpp vs next-plaid

llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. next-plaid has 608 stars, 67 forks, 29 open issues and last shipped 24 days ago. llama.cpp leads on adoption by 21,805% (133,181 vs 608 stars). llama.cpp is written in C++ under MIT; next-plaid is written in Rust under Apache-2.0. llama.cpp has attracted 19% 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 ★ 133K next-plaid ★ 608 category AI & Machine Learning

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Side by side

	llama.cpp	next-plaid
GitHub stars	★ 133K	★ 608
License	MIT	Apache-2.0
Written in	C++	Rust
Last push	2026-11-02	2026-10-10
Forks	⑂ 25K	⑂ 67
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

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 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 next-plaid

NextPlaid & ColGREP NextPlaid is a multi vector search engine. ColGREP is semantic code search, built on it. ColGREP · NextPlaid · Models ColGREP Semantic code search for your terminal and your coding agents. Searches combine regex filtering with semantic ranking. All local, your code never leaves your machine. Quick start Install: Build the index: Search: That's it. No server, no API, no dependencies. ColGREP is a single Rust binary with everything baked in. colgrep init builds the index for the first time. After that, every search detects file changes and updates the index automatically before returning…

read the full next-plaid overview →

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Frequently asked questions

Is llama.cpp or next-plaid more popular?

llama.cpp has 133,181 GitHub stars and next-plaid has 608. 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 (133,181 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.