OpenAI API (ChatGPT) → Ollama
What it saves, what actually moves, what you rebuild — and the thing that catches people.
What it costs, and what it saves
GPT-class API usage at moderate volume runs $50–500/month. Ollama on hardware you own is electricity. On a rented GPU it is roughly $200/month for a card that serves a small team continuously.
Moves cleanly
Your prompts and application logic. Ollama exposes an OpenAI-compatible endpoint, so changing the base URL is often the entire code change.
You rebuild
Prompt tuning. Open models respond differently and prompts tuned for GPT need adjusting — this is the real work.
What OpenAI API (ChatGPT) costs you today
Usage-based per-token billing; ChatGPT Plus/Team/Enterprise seats on top
What actually holds you in
Proprietary models and API surface; your data and cost structure sit entirely on OpenAI's terms.
What you are moving to
Ollama is the simplest way to pull and run open models locally with an OpenAI-compatible API. It handles model management and GPU acceleration out of the box, so a workstation with a modern GPU becomes a private inference server.
Free / self-host (you pay only for your own hardware + power)
Ollama strengths
- One-command model install
- OpenAI-compatible endpoint for drop-in swaps
- Fully offline and private
What you give up
- Quality depends on the model + your VRAM
- You manage your own hardware
The migration, step by step
- 1Install Ollama and pull a model sized to your hardware — a 7B model needs about 8GB of VRAM, a 70B needs roughly 48GB
- 2Point your OpenAI client at http://localhost:11434/v1 and change nothing else
- 3Run your existing evaluation set against both and compare honestly
- 4Tune prompts for the open model rather than expecting parity
- 5Decide per use case; most teams end up routing some traffic each way
The gotcha
Hardware is the constraint everyone underestimates. A 70B model needs roughly 48GB of VRAM and will not run on a consumer card. Teams try a 7B model, find quality inadequate, and conclude local AI does not work when they were simply running the wrong size.
When to stay on OpenAI API (ChatGPT)
You need frontier reasoning quality, or your volume is low enough that the API costs less than the hardware.
Other ways off OpenAI API (ChatGPT)
More Layer 4 migrations
Figures verified 2026-07-04 against vendor pricing pages. Prices change and migrations differ by estate — treat the cost delta as a starting model, not a quote. Rankings and recommendations here are merit-only; affiliate income never changes a verdict. See our methodology.