Local AI Cost Calculator
Is it cheaper to run AI on your own computer than to keep paying for an AI API? Answer three quick questions and see your break-even point.
How the calculator works
It compares two simple running totals. Cloud: your monthly token use multiplied by the price per million tokens, paid every month. Local: the price of the computer up front, plus the electricity it uses each month (with an optional credit for what you could resell it for after two years). The month where the cloud total overtakes the local total is your break-even point.
It also checks whether one machine can actually keep up. Each computer has a typical speed for a mid-size open model; if your usage would keep it busy for more hours than you've allowed, the calculator prices in extra machines rather than pretending one is enough.
Which computer should you look at?
| Machine | Price | Runs | Best for |
|---|---|---|---|
| Mac mini (M4 Pro, 24GB) | $1,399 | Small models (7–14B) | Personal use, very quiet |
| Used RTX 3090 PC (24GB) | ~$1,500 | Small–mid models | Cheapest fast option |
| Mac Studio (M4 Max, 36GB) | $1,999 | Mid-size models (~30B) | Best all-rounder for most people |
| Mac Studio (M3 Ultra, 96GB) | $3,999 | Large models (70B) | Big models, silent |
| NVIDIA DGX Spark (128GB) | $4,699 | Large models (70B+) | Teams and developers |
| RTX 5090 PC (32GB) | ~$5,200 | Mid-size models, fastest | Speed-focused builders |
Prices are typical US prices in October 2026 and change often.
When running AI locally makes sense
- You use AI heavily and steadily, like a team or an app, so the machine is busy most of the day.
- Privacy matters: client documents, health or legal data never leave your office.
- You want predictable costs instead of a bill that grows with every request.
- You need it offline or want to avoid rate limits.
When the cloud is the better deal
- You use AI occasionally, or your usage jumps around a lot.
- You need the very best model for hard reasoning tasks.
- You don't want to maintain hardware or update models yourself.
Curious why so many people are making the switch? Read why cloud AI costs are pushing people toward local hardware, and see what could happen to GPU prices if the AI bubble pops.
Running AI locally: quick answers
Is it cheaper to run AI locally than to use an API?
For heavy, steady use, often yes: a $2,000–$5,000 computer can pay for itself within a year if you'd otherwise spend a few hundred dollars a month on API calls. For light or occasional use, the cloud is almost always cheaper because you only pay for what you use.
How much does it cost to run an AI model at home?
Mostly the up-front price of the computer. Electricity is small: a Mac Studio uses about as much power as a bright light bulb, and even a large graphics-card PC working 10 hours a day typically adds $15–$45 a month to a US power bill.
What computer do I need to run AI locally?
The key spec is memory. 24GB runs small and mid-size open models comfortably; 64–128GB runs the large ones. Apple Silicon Macs share memory with their graphics chip, which makes them a simple choice; PCs with NVIDIA graphics cards are faster per dollar but louder and more power-hungry.
Are local AI models as good as ChatGPT or Claude?
For summarizing, drafting, classifying and routine coding, the best open models are close enough for most people. For the hardest reasoning and the very latest capabilities, the top cloud models still lead. Many teams run routine work locally and send only the tough jobs to the cloud.
How accurate is this calculator?
It's a planning estimate. Cloud prices use public list prices, machine speeds are typical figures for a mid-size open model, and electricity uses the US average rate. Change any number to match your situation; the break-even logic is explained above.