Cryptic Thinking turns the models on your PC into a full AI workstation — chat, vision, documents, agents. No meter running. No prompts leaving your machine. No account, ever.
Once in dollars. Once in data. Both invoices arrive forever.
You pay by the token, by the month, by the seat — for compute your own GPU already does.
Every prompt is a deposit into someone else's asset. You are the pipeline, not the customer.
The fix isn't a better subscription. It's not having a landlord.
The answer to both villains is the same: run the model yourself. Ollama runs open models — Llama, Gemma, Mistral, Qwen and hundreds more — entirely on your own hardware. Free. Unlimited. Nothing leaves your machine; pull the ethernet cable and it keeps answering.
For most daily work — drafting, summarizing, coding help, document Q&A — a local model is all you need. And for the private stuff, it's the only acceptable option.
{"risks":[…]} — rendered with sources below. Nothing was uploaded.Cryptic Thinking is a native Windows app that gives your local models the full workstation treatment — the comfort of ChatGPT, plus abilities a cloud chatbot will never be allowed to have, like executing code and administering your servers.
No Docker. No browser tab. No web server to babysit. Install, click Get LLM List, go.
Every one of these runs on your machine. Read the full deep dive →
Turns the app into an autonomous sysadmin: connects to your servers over SSH, runs commands, reads the output, and reacts on its own. Try asking a cloud chatbot to do that.
Upload .jpg/.png in Generate mode and analyze them with vision models like llava — screenshots included, via the built-in capture button.
Upload .wav/.mp3 — or record straight from the mic — and analyze it with audio-capable models like gemma4.
Local knowledge extraction lets you interrogate large PDFs and text files. Your contracts never see a server.
Import .pdf, .txt and .json directly into the prompt context with one click.
Swap the LLM mid-conversation — draft with a fast 7B, polish with a big one — without losing the thread.
Let the model run local Python through tool calls. Real function calling, on your box.
Structured responses you can actually parse — built for people who pipe AI output into other things.
Run generated Python, PowerShell or Batch scripts directly from the response. Review, click, done.
LaTeX support renders real mathematics instead of ASCII soup.
Generate images locally with x/z-image-turbo and x/flux2-klein.
Temperature, context, system prompts, presets — fine-tune everything the cloud UIs hide from you.
Markdown and HTML rendering with syntax-highlighted code blocks and visible model "thinking".
You already own the hardware. That $240/year buys throttled access to someone else's GPU.
You didn't move to Signal and Proton just to paste your journal into a data harvester.
You run Proxmox for fun. Now run an AI that works for you — literally.
Client files, patient notes, NDA'd code — the cloud was never an option. Local is.
Fair question. Here's how running local models actually shakes out.
| Ollama CLI | Web UIs (e.g. Open WebUI) | Cryptic Thinking | |
|---|---|---|---|
| Setup | ✓ terminal | ◐ Docker / Python server | ✓ install & run, native Windows |
| Runs without a server to maintain | ✓ | ✗ | ✓ |
| Images, audio & files in prompts | ✗ | ✓ | ✓ + screenshots & mic capture |
| Document RAG | ✗ | ✓ | ✓ local extraction |
| Run generated code locally | ✗ | ◐ sandboxed / limited | ✓ Python, PowerShell, Batch |
| Autonomous SSH server agent | ✗ | ✗ | ✓ SSH Bot — exclusive |
| Price | free | free | free |
127.0.0.1:11434 works out of the box.127.0.0.1) and nowhere else. The app works fully offline — the only optional network use is the internet-facing things you explicitly do, like pulling a model.Install Ollama, unzip Cryptic Thinking, click Get LLM List. That's the whole migration.