Set up a free AI engine
Run career-ops for $0 — no Claude subscription or any paid plan required. Free AI engines for career-ops — OpenCode with a free provider, a local model via Ollama, any OpenAI-compatible endpoint, or the built-in OpenRouter runner — and what to do when you run out of tokens mid-search.
No, you do not need a Claude subscription — or any paid plan — to run career-ops. career-ops is free and open source (MIT), and its AI engine can be free too: OpenCode with a free provider, a fully local model via Ollama, any OpenAI-compatible endpoint, or the built-in OpenRouter runner. If you have run out of tokens mid-search, switching to a free engine takes minutes and leaves your CV, pipeline and reports untouched.
career-ops has no paid plans, no tiers, no trials — it is 100% free and MIT-licensed. Any site describing career-ops pricing is describing a different product. The one thing career-ops needs to think is an AI engine — an AI coding assistant that reads its prompts and does the work. That engine can be free too.
With career-ops you bring your own engine and your own key. Nothing runs on career-ops servers — everything happens on your machine. This page shows the free paths, from the easiest to the most hands-on. Pick one and you're ready for the Quick Start.
What am I actually setting up?
Think of career-ops as the recipe and the AI engine as the cook. The recipe is free forever. This page is about getting a cook for free — whether that's a hosted model with a free tier or a model running entirely on your own computer.
Which path is right for me?
| If you want… | Use | Free? | Needs a good computer? |
|---|---|---|---|
| The easiest free start | OpenCode + a free provider | Yes | No |
| Everything 100% offline & private | Ollama (local model) | Yes | Yes — 16GB+ VRAM |
| To reuse a CLI you already have | Its own free tier | If it has one | No |
| The one-command shortcut | npm run or | Yes | No |
Most people should start with OpenCode and a free provider; the other paths are here when you want them.
Path 1 — OpenCode + a free provider (recommended)
OpenCode is a free, open-source AI coding assistant. From career-ops' creator, Santiago Fernández de Valderrama Aparicio: "opencode is top." OpenCode connects to plenty of providers that offer a free tier, so you can run career-ops without spending anything.
Follow the one-line install on opencode.ai. It runs in your terminal, like the other AI CLIs.
Sign up for any provider with a free tier and copy your API key. Popular free options the community uses: OpenRouter (models tagged :free), Google AI Studio (Gemini free tier), and OpenAI-compatible endpoints like Nvidia's free tier. The budget guide keeps the up-to-date list of models that hold up well.
Open OpenCode inside the career-ops folder:
opencodeInside OpenCode, run /connect, choose your provider (for example OpenRouter) and paste your key. Then run /models and pick a free model — on OpenRouter, one tagged :free. OpenCode ignores OPENAI_API_BASE and OPENAI_BASE_URL; /connect and /models are what set it up.
That's it — OpenCode is now your engine. Head to the Quick Start.
Path 2 — A CLI you already have
If you already use a supported CLI — Claude Code, OpenCode, Codex, GitHub Copilot CLI, and more — career-ops works with it, and several of those CLIs ship a free tier. Open your CLI inside the career-ops folder; this path needs no extra setup.
Path 3 — 100% local with Ollama (fully offline)
For zero cloud, zero cost, and total privacy, run the career-ops AI engine on your own machine with Ollama. Nothing leaves your computer.
The trade-off of running career-ops locally is hardware. career-ops asks the model to score jobs across many dimensions and tailor your CV — small models struggle with that.
Pick a model that's big enough
For career-ops on a local model, skip the tiny 7–8B models — they fail the scoring format and produce generic CVs. Use a 32B model or larger (e.g. Qwen 2.5 Coder 32B), which needs a GPU with 16–24GB of VRAM (an RTX 3090/4090, or an Apple Silicon Mac with 32GB+ unified memory). Without such a machine, OpenCode with a free provider (Path 1) is the better free route.
# Install Ollama from ollama.com, then pull a capable model:
ollama pull qwen2.5-coder:32bAfter pulling the model, point your AI CLI (OpenCode works well here) at the local Ollama endpoint, or use the built-in local evaluator described in the budget guide.
Path 4 — The one-command shortcut: npm run or
career-ops ships a built-in runner that routes to OpenRouter's free models with automatic fallback — no CLI configuration to fiddle with. Once you've cloned career-ops and set an OpenRouter key, one command runs the pipeline:
export OPENROUTER_API_KEY="your_free_key_here"
npm run or # runs the full pipeline on free modelsThe npm run or runner also has focused variants — npm run or:scan, or:eval, or:apply — for running a single step.
For developers — tune models & cost
The core career-ops repo's Running on a Budget guide goes deep on maintained model recommendations, per-provider examples, standalone evaluators (node openai-eval.mjs, node ollama-eval.mjs), and token-saving flags. career-ops is fully model-agnostic — point it at any OpenAI-compatible endpoint with zero code changes.
You're ready
Once your engine is set up, continue to the Quick Start — you'll clone career-ops, add your CV, and run your first free scan.
Quick Start
Get started with career-ops in five minutes: install the open-source AI job-search system, open your AI CLI, and evaluate your first job listing. No coding required.
Supported AI CLIs
career-ops is AI-agnostic — it runs on every major AI coding CLI, so you use the assistant you already pay for and never get locked into one vendor. The full, always-current list lives in the core repo.