head to head · open source

llama.cpp vs Spanlens

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. Spanlens has 13 stars, 0 forks, 1 open issues and last shipped 4 days ago. llama.cpp leads on adoption by 988,985% (128,581 vs 13 stars). llama.cpp is written in C++ under MIT; Spanlens is written in TypeScript under MIT. llama.cpp has attracted 18% as many forks as stars, Spanlens 0%. 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 Spanlens ★ 13 category AI & Machine Learning

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Side by side

	llama.cpp	Spanlens
GitHub stars	★ 129K	★ 13
License	MIT	MIT
Written in	C++	TypeScript
Last push	2026-09-17	2026-09-14
Forks	⑂ 23K	⑂ 0
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 Spanlens if

You want the Spanlens feature set and don't need the biggest community
You prefer the MIT license terms
Your stack matches TypeScript
You evaluated both and Spanlens fits your workflow better

full Spanlens 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 Spanlens

Spanlens is an MIT licensed, open source LLM observability and monitoring layer that sits as a drop in proxy in front of OpenAI, Anthropic, and Gemini clients to log every call's cost, tokens, latency, and agent traces, built for developers running LLM applications in production who need more than a provider dashboard's total spend.

read the full Spanlens overview →

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Frequently asked questions

Is llama.cpp or Spanlens more popular?

llama.cpp has 128,581 GitHub stars and Spanlens has 13. llama.cpp has the larger community by that measure.

Are llama.cpp and Spanlens free?

Both are open source. llama.cpp is licensed under MIT and Spanlens under MIT. Neither carries a licence fee.

What is the difference between llama.cpp and Spanlens?

llama.cpp is written in C++ and Spanlens in TypeScript. 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 Spanlens?

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