Локальные LLM
handy-ollama
动手学Ollama，CPU玩转大模型部署，在线阅读地址：https://datawhalechina.github.io/handy-ollama/
★ 2,5 тыс. звёздUnknown
Смотреть руководство →comfyui_LLM_party — проект с открытым исходным кодом из категории «Локальные LLM» от heshengtao (heshengtao/comfyui_LLM_party на GitHub). У него 2 370 звёзд на GitHub и 205 форков, он распространяется по лицензии AGPL-3.0 и последний раз обновлялся на GitHub 29 июля 2026.
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…
One binary or app gets you a working local model setup.
Pick a size that fits your RAM/VRAM; smaller models run on laptops.
Use the built-in UI, or point OpenAI-compatible clients at it.
Airplane mode works — your prompts never leave the device.
Smart compression runs big models on modest hardware.
Works on planes, in basements, behind firewalls.
Swap between hundreds of open models freely.
Existing tools plug in by changing one URL.
Ask questions over your PDFs, notes, and codebases.
Pay nothing per token, ever.
Download the source and move into the project folder.
git clone https://github.com/heshengtao/comfyui_LLM_party.git
cd comfyui_LLM_partyEvery 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 an open-source project at heshengtao/comfyui_LLM_party with 205 forks. Check the repo's contributors and recent commits to see how active maintenance is.
AGPL-3.0 — free to use, including over a network, with source-sharing obligations.
Yes — with no network calls, there's nothing to leak.
Close on many tasks now; frontier cloud models still lead on hard reasoning.
8B models run on 16GB RAM; bigger models want a real GPU.
动手学Ollama，CPU玩转大模型部署，在线阅读地址：https://datawhalechina.github.io/handy-ollama/
🤯 LobeHub is your Chief Agent Operator, organizing your agents into 7×24 operations by hiring, scheduling, and reporting on your entire AI team.
Hundreds of models & providers. One command to find what runs on your hardware.
Agent-native control plane for ComfyUI — generate media in plain chat.
Self-hosted local llm: turns phones into local ai agent runtimes with on-devic.
18 Google Maps tools and 3 agent skills over MCP or CLI.
Другие проекты из категории «Локальные LLM» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если comfyui_LLM_party вам не подходит.
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.
Соседние проекты из категории «Локальные LLM» в каталоге, ближайшие по числу звёзд к comfyui_LLM_party — продолжайте изучать полку по обе стороны от него.
TokenSpeed — a speed-of-light LLM inference engine designed for agentic workloads, with TensorRT-LLM-level performance and vLLM-level usability
Fast Rust scraper that turns web pages into clean data for LLMs.
动手学Ollama，CPU玩转大模型部署，在线阅读地址：https://datawhalechina.github.io/handy-ollama/
Noise-robust subtitle generator powered by Whisper and local ASR models.
Local-first widget tracking token usage and costs across 43+ AI coding tools.
Run controllable pre-trained AI models locally, written in Rust.
Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.