Claude Opus costs $330/month for heavy use. GPT-5 costs $163/month. A Mac Mini M4 Pro costs $1,399. The math isn't complicated, but it's worth doing carefully — because the break-even timing changes depending on which API you're replacing and how intensively you use it.
The baseline: what heavy AI users actually spend
These aren't casual users sending a query here and there. We're talking about professionals who have integrated AI into their daily workflow: lawyers drafting documents, developers writing code, analysts synthesizing reports, business owners running operations through AI.
At that usage level, monthly API costs accumulate quickly. Claude Opus runs $330/month for intensive use; Claude Sonnet around $198/month; GPT-5 around $163/month; GPT-4o around $112/month. These figures reflect real usage patterns from the clients who come to us because they're tired of the monthly bill — and the uncertainty about what it'll be next month.
After break-even, you're running at the cost of electricity — roughly $10/month — with no rate limits, no usage caps, and no subscription to cancel.
The 24-month table
Setup cost: Maai standard setup at $1,999 plus hardware. Mac Mini M4 Pro: $1,399. Total upfront: $3,398.
| API Service | Monthly Cost | 24-Month Total | Break-Even |
|---|---|---|---|
| Claude Opus | $330/mo | $7,920 | ~5 months |
| Claude Sonnet | $198/mo | $4,752 | ~8 months |
| GPT-5 | $163/mo | $3,912 | ~10 months |
| GPT-4o | $112/mo | $2,688 | ~15 months |
The compounding advantage
Month 16 through 24 is when local AI becomes dramatically more economical than cloud alternatives. You've paid off the hardware and the setup. Every query you run is free. Cloud AI doesn't have a break-even — the monthly bill continues indefinitely.
API pricing also changes. OpenAI has repriced its models multiple times. You're exposed to pricing risk you have no control over. Local AI has a different risk profile: you've made the investment upfront, the hardware can be repurposed, and the models are open-source and can be swapped as better ones are released.
What you give up
Fairness requires naming this. The best cloud frontier models — especially for deep multi-step reasoning — are still ahead of what runs locally on 24GB RAM. Cloud AI is also accessible from any device anywhere, without setup.
For workflows where the bottleneck is privacy, unlimited usage, or workflow integration rather than raw reasoning capability, local AI is the better fit.
What you gain
Zero marginal cost per query. No rate limits. Complete data privacy — nothing leaves your hardware. No subscription risk. Runs offline. Consistent performance — no quality changes when the provider silently updates their model. See our pricing page for the full breakdown.
Recommended hardware by use case
For most individuals — lawyers, writers, consultants, small business: Mac Mini M4 with 16GB RAM at $799. Runs 8B models extremely well, handles 14B at good speed.
For heavier users who want larger models: Mac Mini M4 Pro with 24GB RAM at $1,399. Runs 32B models. Our most common setup. See the full model guide for what runs on what hardware.
For teams or organizations that want the best locally-available models: Mac Studio M4 Max with 48GB RAM at $1,999+. Runs 70B models. Significant performance uplift for complex analytical work.
The honest math
If you're spending under $100/month on AI APIs, local AI probably doesn't pay for itself in 24 months. If you're spending $150+/month consistently, local AI is almost certainly cheaper within two years. If you're spending $300+/month, you break even in under six months.
The clients who come to us are usually in the $200–$400/month range and getting frustrated with usage limits, pricing uncertainty, and privacy concerns simultaneously. For them, the economics are clear.