head to head · open source

llama.cpp vs txtai

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. txtai has 12,956 stars, 891 forks, 9 open issues and last shipped 3 days ago. llama.cpp leads on adoption by 892% (128,581 vs 12,956 stars). llama.cpp is written in C++ under MIT; txtai is written in Python under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, txtai 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 txtai ★ 13K category AI & Machine Learning

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Side by side

	llama.cpp	txtai
GitHub stars	★ 129K	★ 13K
License	MIT	Apache-2.0
Written in	C++	Python
Last push	2026-09-17	2026-09-15
Forks	⑂ 23K	⑂ 891
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 txtai if

You want the txtai 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 txtai fits your workflow better

full txtai 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 txtai

txtai is an all in one AI framework for semantic search, LLM orchestration and language model workflows, written in Python and released under the Apache 2.0 license. It lives in the Python machine learning ecosystem and is built on Hugging Face Transformers, Sentence Transformers and FastAPI. The core component is an embeddings database, which is a union of vector indexes (both sparse and dense), graph networks and relational databases. That foundation enables vector search and also serves as a knowledge source for large language model applications.

read the full txtai overview →

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Frequently asked questions

Is llama.cpp or txtai more popular?

llama.cpp has 128,581 GitHub stars and txtai has 12,956. llama.cpp has the larger community by that measure.

Are llama.cpp and txtai free?

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

What is the difference between llama.cpp and txtai?

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

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