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If you handle sensitive documents, customer data or internal notes, local AI can be the safest choice. The model runs on your own hardware and never leaves the building. Here are the best tools for getting started with local AI, ranked by simplicity and flexibility.
| # | Tool | Rating | Price | |
|---|---|---|---|---|
| 1 | LM StudioEasiest to get started | 4,0 Very good | Free | Review → |
| 2 | Jan | 3,8 Good | Free | Review → |
| 3 | OllamaMost popular | 3,8 Good | Freemium | Review → |
| 4 | GPT4All | 3,5 Good | Free | Review → |
| 5 | llama.cppOpen source | 3,5 Good | Free | Review → |
| 6 | whisper.cpp | 3,4 Good | Free | Review → |
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The easiest way to run AI models locally: sleek graphical interface, built-in model catalogue and chat view. Free also for business use since 2025.
Best for: The beginner who wants to try local AI without touching the terminal.
The open-source alternative to LM Studio: chat with local models in a clean interface, completely offline if you want.
Best for: You who want LM Studio's simplicity but with open source.
Run language models (Llama, Mistral, Gemma, etc.) locally with one command. The standard for local AI, but it is terminal-based so some computer experience is required. Local use is free; paid cloud plans (Pro approx. SEK 190/month, Max approx. SEK 950/month) are available for larger models.
Best for: For you who want to run AI models locally without hassle, and who can open a terminal.
Local AI chat with built-in document search (RAG): ask questions about your own files completely offline.
Best for: Asking questions about your own documents without anything leaving the computer.
The engine that has driven the entire local AI wave: extremely optimised C++ code that runs language models on almost any hardware. For those who build themselves.
Best for: Developers who want maximum control and performance.
Transcribe speech to text entirely locally with OpenAI's Whisper models. Sensitive meetings and interviews never leave the computer.
Best for: Transcription of sensitive material that must never leave the computer.
Not necessarily. Smaller models (7B parameters) work on a regular laptop with CPU, while larger models require a dedicated graphics card (GPU) for good performance.
Data does not leave your machine, which makes it considerably easier to defend from a data protection perspective. You still need the right to use the model and respect copyright for training data.
Ollama is the easiest way to get started in the terminal. LM Studio suits you if you want a graphical interface and want to test many models.
