head to head · open source

llama.cpp vs selfhost-ai

llama.cpp has 128,619 GitHub stars, 23,351 forks, 2,464 open issues and last shipped today. selfhost-ai has 933 stars, 235 forks, 0 open issues and last shipped 7 days ago. llama.cpp leads on adoption by 13,686% (128,619 vs 933 stars). llama.cpp is written in C++ under MIT; selfhost-ai is written in Shell under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, selfhost-ai 25%. 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 selfhost-ai ★ 933 category AI & Machine Learning

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Side by side

	llama.cpp	selfhost-ai
GitHub stars	★ 129K	★ 933
License	MIT	Apache-2.0
Written in	C++	Shell
Last push	2026-09-18	2026-09-11
Forks	⑂ 23K	⑂ 235
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 selfhost-ai if

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

full selfhost-ai 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 selfhost-ai

Selfhost AI — Self Hosted AI Automation Platform Deploy 30+ AI and automation tools with a single command. This open source Docker Compose template creates a complete self hosted environment with n8n (workflow automation), Flowise (AI agents), Ollama (local LLMs), vector databases (Qdrant, Weaviate), RAG engines, Supabase, monitoring stack, and more — all pre configured behind Caddy reverse proxy with automatic HTTPS. Plus, optionally import 300+ community workflows during setup! Table of Contents Key Features Why This Setup? What's Included Installation Quick Start and Usage Upgrading Quick Commands Troubleshoot…

read the full selfhost-ai overview →

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Frequently asked questions

Is llama.cpp or selfhost-ai more popular?

llama.cpp has 128,619 GitHub stars and selfhost-ai has 933. llama.cpp has the larger community by that measure.

Are llama.cpp and selfhost-ai free?

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

What is the difference between llama.cpp and selfhost-ai?

llama.cpp is written in C++ and selfhost-ai in Shell. 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 selfhost-ai?

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