head to head · open source

llama.cpp vs openlake

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. openlake has 2,662 stars, 424 forks, 138 open issues and last shipped 3 days ago. llama.cpp leads on adoption by 4,730% (128,581 vs 2,662 stars). llama.cpp is written in C++ under MIT; openlake is written in Rust under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, openlake 16%. 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 openlake ★ 2.7K category AI & Machine Learning

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Side by side

	llama.cpp	openlake
GitHub stars	★ 129K	★ 2.7K
License	MIT	Apache-2.0
Written in	C++	Rust
Last push	2026-09-17	2026-09-15
Forks	⑂ 23K	⑂ 424
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 openlake if

You want the openlake 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 openlake fits your workflow better

full openlake 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 openlake

OpenLake is a Rust storage engine for AI and machine learning infrastructure, aimed at LLM inference and GPU training. It provides distributed storage for GPU workloads and uses io uring to keep accelerators fed during serving and training.

read the full openlake overview →

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Frequently asked questions

Is llama.cpp or openlake more popular?

llama.cpp has 128,581 GitHub stars and openlake has 2,662. llama.cpp has the larger community by that measure.

Are llama.cpp and openlake free?

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

What is the difference between llama.cpp and openlake?

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

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