head to head · open source

llama.cpp vs pegainfer

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. pegainfer has 704 stars, 107 forks, 89 open issues and last shipped yesterday. llama.cpp leads on adoption by 18,164% (128,581 vs 704 stars). llama.cpp is written in C++ under MIT; pegainfer is written in Rust under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, pegainfer 15%. pegainfer 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 pegainfer ★ 704 category AI & Machine Learning

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Side by side

	llama.cpp	pegainfer
GitHub stars	★ 129K	★ 704
License	MIT	Apache-2.0
Written in	C++	Rust
Last push	2026-09-17	2026-09-17
Forks	⑂ 23K	⑂ 107
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 pegainfer if

You want the pegainfer 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 pegainfer fits your workflow better

full pegainfer 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 pegainfer

PegaInfer is a pure Rust and CUDA large language model inference engine that serves models ranging from Qwen3 to Kimi K2 behind an OpenAI compatible API, with no PyTorch or Python runtime in the default serving path.

read the full pegainfer overview →

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Frequently asked questions

Is llama.cpp or pegainfer more popular?

llama.cpp has 128,581 GitHub stars and pegainfer has 704. llama.cpp has the larger community by that measure.

Are llama.cpp and pegainfer free?

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

What is the difference between llama.cpp and pegainfer?

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

Choose llama.cpp if you want the larger community (128,581 stars) or its MIT licence terms. Choose pegainfer if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.