What a Year of AI Tool Subscriptions Actually Costs — and What a Local Setup Gets You
Working out what a year of subscriptions to AI tools like Cursor and cloud APIs costs, and comparing it to a one-time local setup. Where a subscription is worth it, and where a local model pays off more.
AI tool subscriptions creep up on you. One for a code editor, another for a cloud API, a third for automation — each one looks small on its own, but together they add up to a real sum over a year. Let's do the math level-headed and see where a subscription earns its keep, and where a one-time investment in a local setup pays off more.
How to actually count, instead of guessing
Exact prices from services change, so the point isn't the specific numbers — it's the cost model. A subscription is a recurring payment, usually monthly, per tool. Multiply by 12 for the year. With several tools, the amounts stack, and that's where the real bill hides: not "one cheap subscription," but the sum of every subscription over a year.
Check the current prices of your own tools and add up their annual cost. For a lot of people, that sum turns out big enough to actually look at the alternatives.
What you're buying with a subscription
Worth being honest about what you're paying for, or the comparison won't be fair. A subscription to a cloud tool gets you access to top models with no hardware of your own, updates, and nothing to configure. For a lot of people that's reasonable, especially with irregular use.
But a subscription has a downside beyond money too. It's dependence: on the service's availability, on limits, on the payment method. You're paying not just money, but that dependence too.
What a "local setup" costs
Here the cost model is different. A local model computes on your own hardware, so you don't pay per request — it's free. The one-time cost is hardware, but most of the time what you already have is enough: a lot of models run fine on an ordinary laptop.
So instead of "pay every month for every tool," you get "install once and use it." The more actively you work, and the more subscriptions you've accumulated, the more this difference plays in favor of local.
A rule of thumb for the decision. Use AI rarely, with one tool — a subscription is more convenient and probably cheaper than the hassle. Accumulated several subscriptions, work daily, or hit limits often — that's usually where the yearly subscription total outweighs a one-time local setup.
Not "either-or"
An important caveat, so this doesn't turn into an extreme. Going local doesn't cancel the cloud entirely. A sensible setup is keeping your main routine on a free local model and reserving a subscription or cloud API for tasks that genuinely need maximum power. That way you're not paying monthly for what a local model easily handles. In Doka, this is standard: switching between a local and a cloud model happens on the fly.
On power and convenience
No illusions here: top cloud models behind subscriptions are stronger at their peak than local ones, and a subscription removes the need for setup. A local setup takes installing an app once and, maybe, picking a model. But that one-time effort removes both the monthly payments and the dependence on access and billing — for a lot of people, that's a fair trade.
Do the math for a year
Before renewing another subscription, add up the annual cost of all your AI subscriptions and compare it to one local setup that then runs for free. If the sum surprises you, maybe it's time to move some of those tools to a local model. Download Doka for free and see what it covers of your current subscriptions.