Tools for Local/Private AI
AI tools that run entirely on your own hardware — no cloud, no data sharing, no subscriptions. Full privacy and control.
Last updated: February 18, 2026
Tools for Local/Private AI
Run AI on your own machine. No cloud accounts, no data leaving your network, no monthly bills. Everything here is open source or has a fully local option.
See also: The Local Intelligence Stack — our recommended setup with getting-started guide.
Local Language Models
- Ollama — The easiest way to run LLMs locally. One-command install, simple CLI, and an API compatible with OpenAI’s format. Run Llama 3, Mistral, CodeLlama, and dozens more.
- LM Studio — GUI for running local models. Download, chat, and use as a local API server. Good if you prefer a visual interface over CLI.
- llama.cpp — The engine under Ollama. Use directly for maximum control and performance tuning.
Local Image Generation
- ComfyUI — Node-based UI for Stable Diffusion. Maximum control, custom workflows, no content filters. Requires a GPU (8GB+ VRAM minimum, 16GB+ recommended).
- Automatic1111 (Stable Diffusion WebUI) — Browser-based interface for Stable Diffusion. Slightly easier to start with than ComfyUI, fewer advanced features.
- Fooocus — Simplified Stable Diffusion interface. Minimal settings, good results. Best for people who want images without learning ComfyUI.
Local Speech
- Whisper (OpenAI) — State-of-the-art speech-to-text that runs locally.
pip install openai-whisperand transcribe anything. Multiple model sizes for different speed/accuracy tradeoffs. - Piper — Local text-to-speech. Not ElevenLabs quality, but completely free and offline. Good for accessibility and basic narration.
- Bark — Open-source text-to-speech with emotion and multilingual support. More natural than Piper, heavier on resources.
Local Knowledge & Notes
- Obsidian — Local-first markdown notes with a plugin ecosystem. The “Ollama” community plugin lets you chat with a local LLM inside your notes. Your data never leaves your disk.
- Logseq — Open-source, local-first outliner. Block-based references, daily journals, graph view.
Local Coding Assistants
- Continue.dev — Open-source AI coding assistant that works with VS Code. Point it at your local Ollama instance for fully private code completion.
- Tabby — Self-hosted AI coding assistant. Code completion backed by local models.
Hardware Requirements
| Workload | Minimum | Recommended |
|---|---|---|
| Chat (7B model) | 8GB RAM, CPU | 16GB RAM, any GPU |
| Chat (70B model) | 32GB RAM | 64GB RAM or 24GB VRAM GPU |
| Image generation | 8GB VRAM GPU | 16-24GB VRAM GPU |
| Speech-to-text | 8GB RAM, CPU | 16GB RAM, GPU accelerates |
| Everything at once | 32GB RAM, 16GB VRAM | 64GB RAM, 24GB VRAM (RTX 3090/4090) |