LLM local
vLLM
A high-throughput and memory-efficient inference and serving engine for LLMs
★ 93,1k estrellasApache-2.0
Ver la guía →webclaw es un proyecto de LLM local de código abierto de 0xMassi (0xMassi/webclaw en GitHub). Tiene 2.366 estrellas en GitHub y 235 bifurcaciones, se publica bajo la licencia AGPL-3.0 y se actualizó por última vez en GitHub el 23 de septiembre de 2026.
Fast Rust scraper that turns web pages into clean data for LLMs.
Get the Rust-built binary or build from source.
Give it a URL to scrape or crawl.
Get clean markdown or structured data back.
Pipe results to agents via CLI, API, or MCP.
Fast extraction with low resource use.
Runs on your machine, no cloud required.
Clean page conversion for LLMs.
Follow links across whole sites.
Integrate extraction into any stack.
Give AI agents direct scraping tools.
Download the source and move into the project folder.
git clone https://github.com/0xMassi/webclaw.git
cd webclawEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandIt is local-first and open source, so no per-page API fees.
Commercial use is allowed, but network use of modified versions requires sharing source.
Check the docs for rendering capabilities.
Yes, agents can call it through the Model Context Protocol.
Only if building from source; binaries avoid that.
A high-throughput and memory-efficient inference and serving engine for LLMs
High-performance In-browser LLM Inference Engine
Quantization, kernels, runtime and inference engine for mobiles, wearables, smart home and robots
Early proposal and implementation for connecting LLMs to web pages.
Run local LLMs like Llama and DeepSeek right inside your web browser.
Alibaba's lightweight, blazing-fast inference engine for on-device LLMs and edge AI.
Los demás proyectos de LLM local con más estrellas del catálogo de LibreAI: la lista realista de alternativas si webclaw no es lo que buscas.
The simplest way to run open language models on your own machine.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
LLM inference in C/C++
A high-throughput and memory-efficient inference and serving engine for LLMs
🤯 LobeHub is your Chief Agent Operator, organizing your agents into 7×24 operations by hiring, scheduling, and reporting on your entire AI team.
Proyectos de LLM local cercanos en el catálogo, los más próximos en estrellas a webclaw: sigue explorando a ambos lados.
LLM Agent Framework in ComfyUI includes MCP sever, Omost,GPT-sovits, ChatTTS,GOT-OCR2.0, and FLUX prompt nodes,access to Feishu,discord,and adapts to all llm…
Noise-robust subtitle generator powered by Whisper and local ASR models.
TokenSpeed — a speed-of-light LLM inference engine designed for agentic workloads, with TensorRT-LLM-level performance and vLLM-level usability
Run controllable pre-trained AI models locally, written in Rust.
动手学Ollama，CPU玩转大模型部署，在线阅读地址：https://datawhalechina.github.io/handy-ollama/
Let any LLM actually watch a video — frames plus transcript, run locally.
Gratis y abierto: consigue el código fuente, dale una estrella al repositorio y empieza a crear.