head to head · open source

llama.cpp vs llamafarm

llama.cpp has 128,619 GitHub stars, 23,351 forks, 2,464 open issues and last shipped today. llamafarm has 838 stars, 57 forks, 55 open issues and last shipped 3 months ago. llama.cpp leads on adoption by 15,248% (128,619 vs 838 stars). llama.cpp is written in C++ under MIT; llamafarm is written in Python under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, llamafarm 7%. 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 llamafarm ★ 838 category AI & Machine Learning

← all 8884 open source comparisons

Side by side

	llama.cpp	llamafarm
GitHub stars	★ 129K	★ 838
License	MIT	Apache-2.0
Written in	C++	Python
Last push	2026-09-18	2026-06-10
Forks	⑂ 23K	⑂ 57
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 llamafarm if

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

full llamafarm 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 llamafarm

LlamaFarm Edge AI for Everyone Enterprise AI capabilities on your own hardware. No cloud required. LlamaFarm is an open source AI platform that runs entirely on your hardware. Build RAG applications, train custom classifiers, detect anomalies, and run document processing—all locally with complete privacy. 🔒 Complete Privacy — Your data never leaves your device 💰 No API Costs — Use open source models without per token fees 🌐 Offline Capable — Works without internet once models are downloaded ⚡ Hardware Optimized — Automatic GPU/NPU acceleration on Apple Silicon, NVIDIA, and AMD Desktop App Downloads Get started…

read the full llamafarm overview →

More in AI & Machine Learning

Related comparisons

More Machine Learning Infrastructure projects

Compare either of these against the rest of the Machine Learning Infrastructure field.

llama.cpp vs Ollama llama.cpp vs vllm llama.cpp vs GPT4All llama.cpp vs llama_index llama.cpp vs LocalAI llama.cpp vs PageIndex llama.cpp vs Langfuse llama.cpp vs cognee llama.cpp vs taipy llama.cpp vs dagster llama.cpp vs zvec llama.cpp vs langchain4j

Frequently asked questions

Is llama.cpp or llamafarm more popular?

llama.cpp has 128,619 GitHub stars and llamafarm has 838. llama.cpp has the larger community by that measure.

Are llama.cpp and llamafarm free?

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

What is the difference between llama.cpp and llamafarm?

llama.cpp is written in C++ and llamafarm in Python. 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 llamafarm?

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