In AI tools, the unlimited package disappears in favor of credits. For the buyer, the displayed price is no longer sufficient to predict the actual invoice.
By manually recording the prices of 18 consumer video AI tools between April and June 2026, a shift is obvious: at least a third of the panel now operates, partially or totally, with a quota of monthly or annual credits. Generation of a clip, synthetic voice, translation of subtitles, illustrative image: each action consumes credits, and the counter goes down.
The movement has a solid economic logic on the publisher side. Unlike traditional software, where an intensive user costs barely more than an occasional user, each generation of AI has a real infrastructure cost. Unlimited would expose publishers to losses on their most active customers. Credit therefore aligns price with cost. Nothing scandalous in itself. The problem lies elsewhere: in the opacity of the conversion.
Because the real question for the buyer is not: “How many credits for how many euros?” It is rather: “How many credits do I need to produce what I really need?” And this information remains remarkably difficult to obtain before underwriting.
Depending on the tools, a credit can correspond to a minute of analyzed video, to an image generation, to a block of synthesized characters or to an abstract unit whose equivalence varies depending on the function used. Two subscriptions displayed at the same price can thus cover unrelated production volumes.
Added to this is a ratchet effect well known to telecom operators: the unused quota is generally lost, while the excess pushes towards the higher plan. The user finds himself paying for a theoretical volume, calibrated by the publisher, rather than for his actual use. On the panel surveyed, the price differences between plans of the same tool are often explained more by the credit quota than by the functionalities.
Three reflexes allow you to regain control. First, estimate your actual monthly volume before comparing prices: without this data, the comparison between two credit tools makes no sense. Next, look for the credit equivalence table in the publisher’s documentation, and consider its absence as a red flag. Finally, systematically start with the lowest plan, or even free when it exists: one month of actual usage provides better information than a price page on the volume of credits you need.
The credit model is probably not a passing fad. It reflects the real cost structure of generative AI. But until publishers clearly display what a credit produces, the burden of transparency will fall on the buyer.
In a market where tools are multiplying faster than budgets, knowing how to audit a credit system is becoming a purchasing skill in its own right.
Data: manual price list of 18 video AI tools carried out between April and June 2026 on the publishers’ official pages.
