head to head · open source

llama.cpp vs envd

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. envd has 2,230 stars, 168 forks, 139 open issues and last shipped 2 months ago. llama.cpp leads on adoption by 5,666% (128,581 vs 2,230 stars). llama.cpp is written in C++ under MIT; envd is written in Go under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, envd 8%. 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 envd ★ 2.2K category AI & Machine Learning

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Side by side

	llama.cpp	envd
GitHub stars	★ 129K	★ 2.2K
License	MIT	Apache-2.0
Written in	C++	Go
Last push	2026-09-17	2026-07-25
Forks	⑂ 23K	⑂ 168
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 envd if

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

full envd 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 envd

envd is a command line tool for creating container based development environments for AI and machine learning work. It lives in the AI & Machine Learning / Machine Learning Infrastructure ecosystem and is written in Go under the Apache 2.0 license. The project is presented as a reproducible development environment for humans and agents, with topics such as buildkit, docker, llmops, mlops, model serving, code agent, and codex.

read the full envd overview →

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Frequently asked questions

Is llama.cpp or envd more popular?

llama.cpp has 128,581 GitHub stars and envd has 2,230. llama.cpp has the larger community by that measure.

Are llama.cpp and envd free?

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

What is the difference between llama.cpp and envd?

llama.cpp is written in C++ and envd in Go. 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 envd?

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