Inspired by “I replaced ChatGPT, Claude, Gemini, and Perplexity with free open-source alternatives” (XDA).
There’s a particular kind of dread that arrives with the fourth AI invoice of the month. ChatGPT Plus, Claude Pro, Google AI Pro, Perplexity Pro, a coding agent seat — each one defensible on its own, and together they quietly became a car payment.
Here’s the thing that finally pushed me to do something about it: those subscriptions overlap. Spotify and Canva solve completely different problems, so paying for both makes sense. But ChatGPT, Claude, Gemini, and Perplexity all do mostly the same jobs — they’re just marginally better at different corners of them. If you’re paying for several, you’re almost certainly paying for the same capability two or three times. That’s not a budget problem, that’s an architecture problem.
Audit the jobs, not the tools
Before cancelling anything, write down what you actually do with AI on an ordinary day. Mine came out looking like this:
- Drafting, rewriting, summarising — chat-shaped work
- Search that comes back with sources I can check
- A coding agent that can read a repo and make changes
- Quick visual assets — slides, one-pagers, mockups
- Research grounded in documents I supply
Notice what’s not on that list: “use Claude” or “use ChatGPT”. Brands are not jobs. Once the list is about jobs, you can ask a much sharper question per line: is this job ordinary enough that an open-source tool does it, or extreme enough that I genuinely need a frontier model? For most people, most of the week, it’s ordinary.
The chat habit: Jan
The chat-shaped 80% of my usage moved to Jan, and the change was smaller than I expected. Jan’s pitch is blunt — an open-source replacement for the ChatGPT desktop app — and the execution matches. You get conversations, projects, custom assistants with their own instructions, file uploads, and a model hub wired to Hugging Face, so you browse and download quantised models instead of hand-managing GGUF files and hoping your GPU can take it.
Two things matter more than the feature list. First, it speaks MCP, so the same tooling you’d point at a hosted assistant works locally. Second, it’s honest about being a frontend: it’ll happily talk to a dozen remote providers too. That’s the correct framing for the whole exercise — Jan is a client you own, pointed at models you choose. The model is a swappable part, not an identity.
Search with receipts: Vane
The reason I kept a Perplexity subscription was never the chat — it was answers with citations. Vane (formerly Perplexica) is that, self-hosted: a Docker deployment that runs its web search through a SearXNG instance and its reasoning through whatever model you point it at, including one on your own hardware via Ollama.
The good part is that the citations survive the move. You ask a question, you get a summarised answer, and you get the sources it drew from — which is the entire product, as far as I’m concerned. The modes are sensible too: something fast for throwaway questions, something deeper when you actually care. The honest part is the friction: this is a container stack you maintain, not a URL you type. If your Perplexity usage is five queries a month, keep the free tier. If it’s a daily habit and you already run a homelab, the marginal container is cheap.
The coding agent that doesn’t own you: OpenCode
This one stings if you’ve built muscle memory around Claude Code or Codex, because both are excellent — and both lock the agent to one vendor’s models. OpenCode keeps the parts of that workflow that actually matter (planning mode, skills, MCP support, real read-and-edit access across a project) and drops the exclusivity. Claude for the messy refactor where its context handling earns its keep, a cheap or local model for the boilerplate, and you stop paying frontier prices for jobs a small model does fine.
That routing instinct — match the model to the job, not the job to the subscription — is the whole game. It’s the same discipline as not running your CI on the biggest node in the cluster by default.
The remaining seats
Two smaller line items fell out of the same audit. For visual assets, Open Design does prompt-to-design (slides, prototypes, mockups) using whichever agent engine you already run, keeps the output as actual files, and lets you pin a DESIGN.md so assets follow your typography and colours instead of reinventing them per generation. For source-grounded research, Open Notebook covers the bulk of why I used NotebookLM — grounded chat, summaries, and podcast-style audio overviews of material I supply — and I’ve already written about it running it with a local LLM.
What I’d still pay for
None of this means subscriptions are a scam. There are weeks where frontier reasoning, very large context windows, or zero-setup polish genuinely earn the fee, and “free” tools cost you time and hardware like any self-hosted service does. The rule I landed on: cancel the overlap where the job is ordinary; keep paying only where the job is extreme.
Rerun that audit every quarter. The line between ordinary and extreme moves in your favour every few months — and the tools you own don’t invoice you for finding out.