How Many Credits a Lovable Website Actually Costs (106 Projects Measured)
We built 106 websites in Lovable and tracked the credits. The range was 1.5 to 14 credits, roughly 40 cents to $3.50. Prompt length was almost irrelevant. Here is what actually drives the bill.
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We built 106 websites in Lovable and recorded what every one of them cost. The range was 1.5 to 14 credits — about 40 cents to $3.50 — and prompt length explained almost none of it.
A Lovable website costs between 1.5 and 14 credits to build, which is roughly 40 cents to $3.50 at Pro plan rates. That is not an estimate — it is the measured range across 106 projects we generated between June and August 2026, totalling 428 build credits.
The interesting part is what predicts the number, because it is not what most people assume. Prompt length correlates with credit cost at just +0.33, which is weak enough to be close to useless for planning. A 966-character prompt cost us 4.10 credits. A 9,111-character prompt cost 2.00. The longer prompt was less than half the price.
This matters because the standard advice is to keep prompts short to save credits. Our data says that advice is wrong, and following it costs you output quality for no financial benefit.
What that is in real money
Credits are an abstraction, so here is the conversion. Lovable's Pro plan is $25 a month for 100 credits, which puts a credit at 25 cents. Annual billing brings the plan to about $21 a month, or roughly 21 cents a credit.
At that rate, the numbers in this study look like this:
Cheapest site in the set — 1.5 credits, about $0.38.
Median site — around 4 credits, about $1.00.
Most expensive site — 14 credits, about $3.50.
All 106 projects together — 428 credits, about $107.
A single-page marketing website for a dollar is the headline most people miss while they are worrying about credit counts. The reason to care about the difference between 1.5 and 14 is not the three dollars — it is that a hundred-credit monthly allowance builds sixty cheap sites or seven expensive ones.
One caveat on the conversion: plan prices and credit allowances change, and Lovable has revised both. Treat 25 cents a credit as accurate for the Pro plan as of August 2026 rather than as a permanent constant.
What we measured
Every project in this dataset is a single-page marketing website generated from a written prompt in Lovable, between June and August 2026. All of them were built from prompts published on websiteprompts.ai, so the inputs are public and the outputs are comparable.
For 44 of the projects we could match the Lovable project back to the exact prompt that produced it and measure that prompt's characteristics: character count, word count, number of code blocks, number of npm dependencies specified, and number of described interactive components. Those 44 are the basis for every correlation below.
Prompt length barely affects the cost
Here are four projects from the dataset, chosen because they break the intuition completely:
966-character prompt — a short, plain-language brief with no code examples and no named dependencies. Cost: 4.10 credits, about $1.03.
8,182-character prompt — a full design system, twelve sections and complete written copy. Cost: 1.50 credits, about $0.38. The cheapest project in the entire set.
9,111-character prompt — similar length, similar structure, one animated SVG element. Cost: 2.00 credits, about $0.50.
10,754-character prompt — a car rental site with a date-driven search bar, a filterable fleet grid and an accordion. Cost: 14.00 credits, about $3.50. The most expensive project in the entire set.
The two nine-thousand-character prompts cost less than the thousand-character one. The correlation coefficients across all 44 matched projects are consistent with that: length +0.33, word count +0.35, dependencies +0.33, code blocks +0.27. None of them is strong enough to plan around.
There is a second comparison worth putting on the record. Ten of our older prompts had a median length of 1,569 characters and a median cost of 4.10 credits. Thirty-four newer prompts had a median length of 10,480 characters and a median cost of 4.65 credits. Six times the prompt length produced 13% more cost, or about thirteen cents.
What actually drives the cost
The four most expensive projects in the dataset have almost nothing in common on paper — different industries, different lengths, different visual styles. They have one thing in common in practice.
14.00 credits, about $3.50 — car rental site. A search bar that computed day counts from selected dates, plus a filterable vehicle grid, plus an accordion, plus a date-picker library.
9.50 credits, about $2.38 — guitar shop. A multi-filter product grid with a range slider component.
7.90 credits, about $1.98 — bed and breakfast. A room selector with a date-picker library attached.
7.10 credits, about $1.78 — window cleaning. A live price calculator with a range slider component.
Every one of them combines a widget that recomputes a number as the user changes an input with a third-party UI component library. That is the pattern.
The four cheapest tell the same story from the other end. A bowling alley at 1.50 credits, a butcher at 2.00, an art gallery at 2.50 and a bike shop at 2.90 — between 38 cents and 73 cents each. All four are carried by typography, photography and layout rather than by logic. None of them asks the AI to compute anything.
Why third-party components are so expensive
Naming a UI library in a prompt looks like a shortcut. It is the opposite. Every library you specify becomes an install, a set of imports, a wiring step and a type contract the model has to satisfy. When any part of that fails, you send a follow-up message asking for a fix, and follow-up messages cost credits too.
That is the mechanism we believe explains the tail. A 14-credit project is almost certainly not a single generation. It is one build plus several rounds of correction.
Native HTML solves most of it. A date input, a range input and a details element cover the majority of what these libraries were doing, cost nothing to install, and cannot fail at the integration step because there is no integration step.
Lovable changed how credits are counted
Part of what people are noticing is not their own prompts at all. In July 2025 Lovable moved from a flat one-credit-per-message model to complexity-weighted pricing, where a simple change costs around half a credit and a complex generation costs closer to two.
Under a flat model, an ambitious prompt and a simple one cost the same. Under a weighted model, ambition is billed. The same prompt that cost one credit in early 2025 can legitimately cost three now without anything about it having changed.
What this data cannot tell you
Three limitations, stated plainly, because a study that hides them is not worth reading.
First, the sample is 44 matched projects, not 106. The remaining projects could not be reliably matched back to a specific prompt.
Second, credits are charged per message, and we did not log message counts. We cannot separate an expensive first generation from a cheap generation followed by four rounds of fixes. The pattern we found in the expensive tail is consistent with the second explanation, but consistency is not proof.
Third, every project here is a single-page marketing site. None of this generalises to applications with authentication, databases or payment flows.
Five rules for a cheaper prompt
Based on what the data supports rather than on what sounds sensible:
Do not shorten your prompt to save money. It does not work, and it costs you specificity, which is the only thing that reliably improves the output.
Name no UI libraries. Write native HTML inputs into the prompt instead. This is the single clearest lever in the dataset.
Allow one interactive element, not three. The expensive projects all stacked a calculator on a filter on an accordion.
Cut long data arrays. A twelve-item menu written out in full is twelve items the model has to type. Four items and a note that the pattern repeats produces the same design.
Prefer visual complexity to logical complexity. Large type, real photography, texture and motion are cheap to generate and are what people actually judge a website on.
That last rule is the one that surprised us most. Across the dataset, the projects that look best are also the projects that cost least. Making a site beautiful and making it cheap turned out to be the same decision.
