Run AI on your own hardware with full privacy. This guide covers setup, GPU tiers, and your first app.

Why Run AI Locally?

Cloud AI services are convenient, but they come with trade-offs: monthly fees, data exposure, and rate limits. Running AI locally means your prompts, images, and voice recordings never leave your machine. You pay once for hardware and run unlimited inference forever.

Privacy is the obvious benefit, but there are others. Local inference has zero latency variability—no waiting for a server halfway around the world. You can work offline. And you can run models that cloud providers refuse to host.

The local-first architecture behind Thumper-Run was built specifically for this use case.

What You Need

The minimum setup for useful local AI:

CPU: Any modern x86_64 or ARM processor (M1+ Mac, Ryzen 5+, Intel 12th gen+)
RAM: 16 GB minimum, 32 GB recommended
GPU: Optional but strongly recommended. Even a 6 GB card (RTX 2060, RX 6600) unlocks image generation.
Storage: 50 GB free for models and app data. An SSD is strongly preferred.

No GPU? You can still run language models on CPU with Ollama. A Ryzen 7 produces usable chat responses at 10–20 tokens per second. See the hardware guide for detailed benchmarks.

Quick Start

Download Thumper-Run for your platform (Linux, macOS, Windows)
Open the app and let the hardware scan detect your GPU and available VRAM
Browse the App Catalog and install your first app
Click Launch—Thumper handles dependencies, model downloads, and GPU configuration

The entire process from download to first inference typically takes under ten minutes.

Choose Your First App

Not sure where to start? Here are the most popular choices by category:

Chat: Open WebUI + Ollama – a private ChatGPT replacement
Images: ComfyUI – node-based image generation with Stable Diffusion
Voice: OpenVoice – clone your voice with a 30-second sample
Code: Vibe Coding Agent – generate and edit code with a local AI
Video: LTX-Video – text-to-video on consumer hardware

GPU Tiers

Your GPU determines what you can run and how fast:

No GPU (CPU only) – Text chat (Ollama), small language models, text-to-speech
6–8 GB VRAM – SD 1.5 image generation, 7B parameter LLMs, voice cloning
10–12 GB VRAM – SDXL, 13B LLMs, real-time voice chat, music generation
16–24 GB VRAM – FLUX, 30B+ LLMs, video generation, 3D mesh generation
48 GB+ VRAM – 70B LLMs at full precision, training and fine-tuning

Thumper-Run's GPU detection automatically recommends apps compatible with your hardware.

What Can You Do?

The local AI ecosystem in 2026 covers nearly every creative and productivity task:

Generate images from text or sketches
Chat with uncensored language models
Clone voices and generate speech
Create music from text descriptions
Generate video clips from prompts
Convert images to 3D models for games and printing
Search your documents with private RAG pipelines
Write and debug code with AI agents
Fine-tune models on your own data with complete privacy

Each of these workflows runs entirely on your hardware. See our use cases for detailed tutorials.

Cost vs Cloud

A quick comparison for someone generating 100 images per day:

Cloud (Midjourney Pro): $60/month = $720/year
Local (RTX 4060 Ti): ~$400 one-time, $0/month after that

Local breaks even in under 7 months and is free forever after. For heavier usage—video generation, LLM chat, voice synthesis—the savings compound quickly. Read the full cost analysis for more scenarios.

Ready to try it? Download Thumper-Run free →