Technology · Product
llama.cpp
Product · Catalog tech@1
LLM inference in C/C++ on local hardware.
- Categories
- Matched as
- ggml
- llama-cpp
- llama.cpp
- llamacpp
Momentum
Each signal is ranked as a percentile among the technologies that have it. A signal without enough history is not counted, and never shown as zero. How momentum works
Momentum
Collecting0 of 5 signalsNo score yet. Momentum is published only when at least 2 of the 5 signals have history. llama.cpp has 0, so there is no single number: each signal is shown on its own below. It is not a zero, and nothing is estimated in its place.
Snapshot OCT 24, 2026 · Scoring tech@1
- Official repository stars
- Collecting
- Star growth needs repository snapshots 30 days apart.130,136 stars now
- Member repository stars
- Collecting
- Star growth needs repository snapshots 30 days apart.0 new members in 30 days
- Package adoption
- Not published by its registries
- Its packages’ registries publish no adoption figure, so there is nothing to grow.
- Open models
- No official models
- No official model on Hugging Face, so this signal does not apply.
- News
- Collecting
- News counts once there are 3 events across the last 60 days; it has 1.0 in the last 30 days · 1 in the 30 before
Adoption by registry
The growth of llama.cpp’s own packages, one row per registry in that registry’s own unit. Registries count different things over different windows, so they are never added together.
No registry has two observations of llama.cpp’s own packages about 30 days apart yet, so there is no growth to show. Nothing is estimated in its place.
News activity
- Events · 7 days
- 0published events that mention it
- Events · 30 days
- 0published events that mention it
- Previous 30 days
- 1events in the 30 days before
Momentum history
Momentum history starts OCT 8, 2026. A chart appears once two daily snapshots carry a score; none does so far.
Repositories
Official 1
- ggml-org/llama.cpp
LLM inference in C/C++
130.1K stars
Members 61repositories tagged with one of its aliases, most-starred first
- Osmantic/ODS
ODS V3 Pre-Release: Public testing and refinement ahead of the official V3 launch. Turn your PC, Mac, or Linux box into a private AI server.
7K stars
- cactus-compute/cactus
Quantization, kernels, runtime and inference engine for mobiles, wearables, smart home and robots.
6.1K stars
- Michael-A-Kuykendall/shimmy
⚡ Pure-Rust WebGPU inference engine — OpenAI-API compatible, GGUF native, runs on any GPU. No Python. No llama.cpp. Single binary.
5.9K stars
- mostlygeek/llama-swap
Reliable model swapping for any local OpenAI/Anthropic compatible server - llama.cpp, vllm, etc
5.8K stars
- gptme/gptme
Your agent in your terminal, equipped with local tools: writes code, uses the terminal, browses the web. Make your own persistent autonomous agent on top!
4.4K stars
- JohnSnowLabs/spark-nlp
State of the Art Natural Language Processing
4.2K stars
- SciSharp/LLamaSharp
A C#/.NET library to run LLM (🦙LLaMA/LLaVA) on your local device efficiently.
3.8K stars
- twinnydotdev/twinny
Open-source AI coding assistant for VS Code. Code completion, chat, edits and reviews with local or hosted models. Your models, your infrastructure.
3.7K stars
- PrismML-Eng/Bonsai-demo
Bonsai Demo
3.3K stars
- Josh-XT/AGiXT
AGiXT is a dynamic AI Agent Automation Platform that seamlessly orchestrates instruction management and complex task execution across diverse AI providers. Combining adaptive memory, smart features, and a versatile plugin system, AGiXT delivers efficient and comprehensive AI solutions.
3.2K stars
- SilasMarvin/lsp-ai
LSP-AI is an open-source language server that serves as a backend for AI-powered functionality, designed to assist and empower software engineers, not replace them.
3.2K stars
- 0xShug0/audio.cpp
An all-in-one, pure C++ inference engine for audio models, powered by ggml. Supports TTS, STT, VAD, voice conversion, music generation, and more, with highly optimized performance. No Python dependency.
3.2K stars
Packages
“Is” packages are llama.cpp itself; ecosystem packages depend on them. The two are counted separately and never added together. Adoption is each registry’s own figure, with its percentile within that registry.
Is 1the technology itself, most-adopted first
- gguf
Read and write ML models in GGUF for GGML
Not published by PyPI
Ecosystem 12packages that depend on it, most-adopted first
- ai-dynamo-vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
Not published by PyPI - freetoken
Local MoE-offload LLM inference runtime with OpenAI- and Anthropic-compatible APIs
Not published by PyPI - gen-worker
A library used to build custom functions in Cozy Creator's serverless function platform.
Not published by PyPI - invokeai
A full-featured AI-assisted image generation environment designed for creatives and enthusiasts.
Not published by PyPI - lsglang
SGLang is a fast serving framework for large language models and vision language models.
Not published by PyPI - sglang
SGLang is a fast serving framework for large language models and vision language models.
Not published by PyPI - sglang-kt
SGLang is a fast serving framework for large language models and vision language models.
Not published by PyPI - vllm-cpu-amxbf16
vLLM CPU inference engine (AVX512 + VNNI + BF16 + AMX optimized)
Not published by PyPI - vllm-cpu-avx512
vLLM CPU inference engine (AVX512 optimized)
Not published by PyPI - vllm-cpu-avx512bf16
vLLM CPU inference engine (AVX512 + VNNI + BF16 optimized)
Not published by PyPI - vllm-omni
A framework for efficient model inference with omni-modality models
Not published by PyPI - vllm-xft
A high-throughput and memory-efficient inference and serving engine for LLMs
Not published by PyPI
Latest news the latest event that mention it
- 32d agoSEP 22, 2026