Lokale LLMs
Unsloth
Run and fine-tune LLMs and diffusion models locally — faster training, smaller memory footprint.
★ 77,2 Tsd. SterneApache-2.0
Anleitung ansehen →Ollama ist ein Open-Source-Projekt aus der Kategorie Lokale LLMs von ollama (ollama/ollama auf GitHub). Es hat 182.098 Sterne auf GitHub und 18.090 Forks, wird unter der Lizenz MIT veröffentlicht und wurde zuletzt am 3. Oktober 2026 auf GitHub aktualisiert.
The simplest way to run open language models on your own machine.
macOS and Linux use the install script; Windows uses a one-line PowerShell command. Desktop downloads exist too.
Type ollama run followed by a model name — your first run downloads the weights, then you are chatting.
Point coding agents, chat apps, and your own code at Ollama's local API instead of a cloud endpoint.
Pull new models anytime with ollama pull and switch between them freely.
macOS, Windows, Linux, and Docker — up and running in about a minute.
Llama, Qwen, Gemma, DeepSeek, gpt-oss, Kimi, GLM, MiniMax, Mistral, and more, in multiple sizes.
An OpenAI-style local endpoint your apps and agents can call with zero cloud dependency.
Works with Claude Code, Codex, Copilot CLI, OpenCode, OpenClaw, and other harnesses.
Turn it into a personal assistant across WhatsApp, Telegram, Slack, and Discord.
First-party Python and JavaScript libraries plus a big community ecosystem.
macOS / Linux: run the install script. Windows: run the PowerShell one-liner.
curl -fsSL https://ollama.com/install.sh | sh
# Windows PowerShell:
irm https://ollama.com/install.ps1 | iexStart chatting with any model from the library.
ollama run gemma4Call the local API from your app, or launch an integration such as a coding agent.
ollama launch claudeLocal models also power the security shelf: Pentest Harness bills itself as a heaven for hackers — a penetration-testing harness built to run on local models rather than cloud APIs. Also on this shelf: entroly — Cut AI context cost with reversible, byte-exact compression. Readers working through the Local LLM shelf also stop at kotaemon, an open-source RAG-based tool for chatting with your documents.
Yes — MIT licensed, free for personal and commercial use, with no account required.
No — it runs on CPU too, though a GPU makes larger models much faster. Smaller models fly even on modest machines.
Ollama is the easiest way to run models. Unsloth adds training and fine-tuning. Many people use Ollama to run what Unsloth helped them train.
The library lists sizes and strengths per model — start small (a few GB) and scale up if your machine handles it.
Yes — the local API plus official Python/JS libraries make it a popular backend for indie AI apps.
Run and fine-tune LLMs and diffusion models locally — faster training, smaller memory footprint.
A one-click browser for open-source AI apps — discover, install, and run anything.
Alibaba's open voice models: expressive, streaming-capable speech with free-form voice design.
Atomic Agent is a local-first AI agent. Runs open-weight models on your own machine via llama.cpp.
Run AI models locally on your machine with node.js bindings for llama.cpp. Enforce a JSON schema on the model output on the generation level
BitNet — Microsoft's official inference framework for 1-bit large language models, running fast on ordinary CPUs, MIT
Die anderen Projekte der Kategorie Lokale LLMs mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls Ollama nicht das Richtige ist.
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.
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
Verwandte Projekte der Kategorie Lokale LLMs im Katalog, die Ollama bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
Find the best local models for your hardware — and how to run them.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
Token efficient translation utility built on ChatGPT or any OpenAI compatible LLM.
LLM inference in C/C++
Self-hosted control plane: approve or block rogue agent calls.
A high-throughput and memory-efficient inference and serving engine for LLMs
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.