the FBI can read your ChatGPT history. they can't read mine.

The FBI just retrieved deleted Signal messages through iPhone notification data. That was supposed to be the most private messenger available.

Your ChatGPT conversations? Those sit on OpenAI's servers. Subpoena-ready. Every prompt you've written, every document you've pasted, every code snippet you've shared. OpenAI's privacy policy explicitly states they can share data with law enforcement.

Same goes for Claude, Gemini, Copilot. Every cloud AI provider stores your conversations. Some for 30 days, some for "model improvement," some indefinitely. And when a court order arrives, they comply. They have to.

I stopped using cloud AI for anything that matters six months ago.

What I Actually Use

Everything runs on my machine. No server, no API calls, no conversation logs on someone else's infrastructure.

For text/chat: Ollama running Qwen 3.5 or Gemma 4. The model weights live on my SSD. The conversation exists in RAM while I'm using it, and nowhere else.

For code: A local coding agent with MCP tools — file read/write, shell execution, web search. It reads my codebase directly from disk. No code leaves my network.

For images: ComfyUI with FLUX and Z-Image. Prompts and generated images stay on my hard drive.

For video: FramePack F1 — image-to-video on 6 GB VRAM.

All of this runs through one app: Locally Uncensored. It auto-detects whatever backend you have installed, or walks you through setup if you have nothing. One desktop app, everything local.

The Real Cost of "Free" Cloud AI

People think ChatGPT Plus at $20/month is cheap. But the actual cost isn't money — it's that every conversation becomes training data, legal evidence, and a data breach waiting to happen.

The Mistral breach just exposed internal data. OpenAI employees have warned about internal security practices. Anthropic got blacklisted by the US government. Disney just cancelled a billion-dollar OpenAI deal over trust concerns.

These aren't hypothetical risks. They're this week's headlines.

The Local Setup Is Easier Than You Think

Five years ago, running AI locally meant compiling CUDA kernels and hand-editing config files. Today:

1. Install Ollama (one command)
2. Pull a model: ollama pull qwen3.5:9b
3. Open Locally Uncensored, it auto-detects Ollama
4. Chat, code, generate — everything stays on your machine

Total time: under 10 minutes. Total recurring cost: $0. Total data sent to the cloud: zero bytes.

No, Local Models Aren't "Worse"

Qwen 3.5 35B matches GPT-4 on most benchmarks. Gemma 4 27B has native vision and tool calling. GLM 5.1 (754B, MIT license, released this week) leads SWE-Bench Pro.

The "cloud models are better" argument made sense in 2023. In 2026, it's marketing.

GitHub: PurpleDoubleD/locally-uncensored — AGPL-3.0, Tauri v2, no telemetry.