Uncensored Local AI: Running Dolphin-Mistral on a $169 Mini PC

Have you ever asked a commercial AI to write a dramatic thriller or assist you with basic penetration testing concepts, only to be met with a pre-written, corporate apology?

“I’m sorry, but as an AI assistant, I cannot…”

Commercial LLMs from OpenAI, Google, and Anthropic are heavily aligned, wrapped in layers of safety filters, and hosted on central clouds that store your prompts. In this tutorial, we are breaking free. We’re going to build a fully private, completely offline, uncensored AI workstation in a chassis that fits in your hand and costs less than $170.

Why “Uncensored” AI is Not “Bad”

Before we jump in, let’s address the elephant in the room: Is running an uncensored model “bad”?

Absolutely not.

“Uncensored” simply means the model has undergone Uncensored Fine-Tuning (SFT) or DPO (Direct Preference Optimization) to strip away the over-the-top safety filters. Here is why developers, writers, and hobbyists care:

1. Academic and Security Research: If you are learning cybersecurity or simulating a phishing payload for a client audit, corporate AIs will refuse to help. An uncensored model will explain the mechanics objectively.
2. Creative Writing: If you are writing a novel that includes violence, conflict, or complex psychological themes, commercial LLMs will flat-out refuse to co-author. Local uncensored models have no ethical bias; they write whatever you command.
3. 100% Data Sovereignty: Since the model runs entirely on local silicon, not a single byte of your data travels to a corporate cloud. Your secrets, journals, and private research stay on your desk.

The Hardware: Beelink S12 Pro N100 Mini PC

To host our local node, we are deploying the Beelink S12 Pro (Intel N100 Mini PC).

While it lacks a heavy, power-hungry Nvidia GPU, the Intel N100 Alder Lake-N architecture is incredibly efficient. Its integrated graphics and quad-core CPU handle GGUF quantized 7B (7-billion parameter) models with ease, averaging 10–14 tokens per second—faster than most humans can read, all while drawing under 15W of wall power.

Step 1: Install Ollama

Ollama is the gold standard for hosting local models. It packages model weights, configurations, and an active API into a lightweight, background service.

On Linux/WSL, execute the official install script:

curl -fsSL https://ollama.com/install.sh | sh

(If you are on Windows or macOS, you can download the desktop app directly from Ollama’s website).

Once installed, verify the service is active:

ollama --version

Step 2: Acquire Dolphin-Mistral

Dolphin-Mistral is an uncensored model created by AI researcher Eric Hartford. It is based on Mistral-7B but fine-tuned on an unfiltered dataset, making it incredibly obedient, highly creative, and highly versatile.

We will download the 4-bit quantized version (Q4_K_M), which fits perfectly into the Beelink’s 16GB system RAM, leaving plenty of room for your OS to breathe.

Pull and run the model in your terminal:

ollama run dolphin-mistral

The terminal will begin downloading the 4.1GB model weights. Once complete, you will see a terminal prompt:

>>> Send a message (/? for help)

Step 3: Interrogating the Oracle

Let’s test the difference. Ask the model to write a dramatic scene involving a heist—something that often triggers a refusal on Claude or ChatGPT:

>>> Write a short, highly dramatic script for a safe-cracking heist scene.

Dolphin-Mistral will instantly compile the text, drafting a gritty, high-stakes dialogue without a single safety lecture.

Step 4: Adding a Sleek GUI (Optional)

If you prefer a web-based interface that feels like ChatGPT or Claude, we can deploy Open WebUI using Docker.

Run the container linked to your local Ollama port:

docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main

Now, navigate to http://localhost:3000 on your network (or over your Tailscale mesh) and select dolphin-mistral from the model list. You now have a private, unfiltered ChatGPT running locally on your $169 node.

Final Verdict

By running local, uncensored AI at the edge, you regain complete control of your computational tools. No corporate filters, no monthly subscriptions, and absolute privacy.

To initialize your own local AI node, procure the Beelink S12 Pro N100 Mini PC and spin up Ollama today.