head to head · open source

llama.cpp vs InferenceX

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. InferenceX has 1,718 stars, 299 forks, 254 open issues and last shipped yesterday. llama.cpp leads on adoption by 7,384% (128,581 vs 1,718 stars). llama.cpp is written in C++ under MIT; InferenceX is written in Python under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, InferenceX 17%. InferenceX 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 InferenceX ★ 1.7K category AI & Machine Learning

← all 8884 open source comparisons

Side by side

	llama.cpp	InferenceX
GitHub stars	★ 129K	★ 1.7K
License	MIT	Apache-2.0
Written in	C++	Python
Last push	2026-09-17	2026-09-17
Forks	⑂ 23K	⑂ 299
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 InferenceX if

You want the InferenceX 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 InferenceX fits your workflow better

full InferenceX 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 InferenceX

InferenceX is an open source continuous inference benchmark research platform written in Python under the Apache 2.0 license. It lives in the machine learning infrastructure ecosystem, where teams evaluate large language model serving frameworks and accelerator systems. Formerly named InferenceMAX, the project maintains a public dashboard and a benchmark repository that track performance as inference software and hardware change.

read the full InferenceX 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 InferenceX more popular?

llama.cpp has 128,581 GitHub stars and InferenceX has 1,718. llama.cpp has the larger community by that measure.

Are llama.cpp and InferenceX free?

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

What is the difference between llama.cpp and InferenceX?

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

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