ローカルLLM
lemonade
Discover and run local AI apps, serving optimized LLMs from your own GPU and NPU.
★ 5.8k スターApache-2.0
ガイドを見る →GPT4Allは、nomic-aiが公開しているオープンソースのローカルLLMプロジェクトです（GitHub: nomic-ai/gpt4all）。GitHubスターは77,360、フォークは8,262で、MITライセンスの下で公開されています。GitHubでの最終更新は2025年5月27日です。
GPT4All — run local LLMs on any device: a free desktop chat client and Python SDK that run open models entirely on your CPU, no GPU or cloud required
Download the free installer for Windows, macOS or Linux from nomic.ai/gpt4all.
In the app, open the model browser and pick one that fits your RAM — the catalogue shows sizes and requirements; downloads are a few GB each.
Start chatting fully offline, or add a folder under LocalDocs to ask questions about your own files with local retrieval.
Quantised GGUF models run usefully on ordinary laptops — no GPU required, which is the whole point.
Model browser, chat UI and settings in one free app; nothing to configure in a terminal.
Point it at document folders and chat with their contents using retrieval that never leaves the machine.
Python and Node bindings, plus an OpenAI-style local server, for building on the same models.
The route most people take — one download, then pick a model in-app.
https://nomic.ai/gpt4allFrom the README: install the bindings and load a model in a few lines.
pip install gpt4all
from gpt4all import GPT4All
model = GPT4All("Meta-Llama-3-8B-Instruct.Q4_0.gguf")
with model.chat_session():
print(model.generate("How can I run LLMs efficiently on my laptop?", max_tokens=1024))The desktop app can serve an OpenAI-compatible API on your machine for other tools to use.
Enable "Enable Local Server" in GPT4All settingsNomic AI (nomic-ai/gpt4all on GitHub), the company behind the Atlas data tool.
Yes — the app, SDKs and ecosystem are MIT licensed and free for commercial use. The models you download carry their own licences — check each one.
No. GPT4All is built for CPU inference with quantised models; a GPU speeds things up where supported, but a modern laptop is enough.
Against Ollama, GPT4All gives non-technical users a full graphical app and document chat out of the box, while Ollama is CLI-first and stronger as a developer server. Against LM Studio, the difference is licensing and openness: GPT4All is MIT open source, LM Studio is a polished free-but-closed app.
Install the desktop app, download a recommended model from the in-app browser, and chat — offline from the first message.
Discover and run local AI apps, serving optimized LLMs from your own GPU and NPU.
Elegant AI chat client with workspaces, plugins, and local-first sync.
Find the best local models for your hardware — and how to run them.
Google DeepMind's Gemma open-weight LLM library — install, load and chat with Gemma models in Python.
Lightweight inference engine for running LLMs efficiently on any device.
Run local LLMs like Llama and DeepSeek right inside your web browser.
LibreAIカタログに掲載されたローカルLLMプロジェクトの中で最もスターの多いもの — GPT4Allが合わなかった場合に検討したい、現実的な候補リストです。
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カタログの中でGPT4Allとスター数が近いローカルLLMプロジェクト — 前後の棚もそのまま見て回れます。
🤯 LobeHub is your Chief Agent Operator, organizing your agents into 7×24 operations by hiring, scheduling, and reporting on your entire AI team.
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