Guides / free trial llm cost
What your free trial costs in model spend, per customer acquired
Free trial LLM cost is the model spend consumed by users who haven't paid, which makes it customer acquisition cost that arrives on a provider invoice rather than in an ad account. Divide it by your conversion rate for the real figure. Culpa, a local-first LLM cost, margin, and forecast ledger, prices trial calls and attributes them per account.
Why this happens
A free trial with an LLM behind it spends real money on people who may never pay, and that spend is almost never counted where it belongs. Marketing tracks CAC from ad platforms. Finance tracks model spend as cost of goods sold. Trial compute falls between them: it behaves like acquisition cost, since its purpose is converting a prospect, and it arrives looking like COGS, because it comes on the same invoice as paying customers' usage. The arithmetic that matters divides trial spend by conversions rather than by trials, because the users who churn are paid for by the ones who convert. At an 8% conversion rate every conversion carries 12.5 trials, its own and the 11.5 that went nowhere. There's a second, sharper version of this problem: a trial that lets a user run unlimited generous requests is a line of credit issued to anyone with an email address, and the only defence that works is knowing what each trial account has consumed while it's consuming it. Caps and quotas only bind if something is counting.
What this usually looks like
- Your CAC number contains ad spend and no compute.
- Trial and paid usage arrive on the same invoice and nothing separates them.
- One trial account consumed more than your median paying customer.
- Nobody can say what a trial costs you before it converts.
- You extended trial limits to improve conversion and never priced the change.
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Mistakes that cost the most
| Mistake | Why it hurts | Do instead |
|---|---|---|
| Leaving trial compute out of CAC. | It's money spent to acquire a customer, so excluding it understates acquisition cost and overstates payback. | Add trial model spend to CAC, divided by conversions rather than by trials. |
| Dividing trial spend by the number of trials. | It reports what a trial costs, not what a customer costs, and only the second one funds itself. | Divide by conversions, because converters carry the compute of everyone who left. |
| Running a generous trial with no per-account visibility. | An unlimited trial is credit issued on an email address, and the bill arrives before anyone notices. | Meter each trial account individually and know the distribution, not just the total. |
| Setting a trial limit from an average. | Trial usage is heavily skewed, so an average limit is generous for most and free rein for the tail. | Set limits from the distribution, and watch the top percentile rather than the mean. |
Run this check tonight
- Add up last month's model spend from accounts that have never paid.
- Divide it by the number of trials that converted, not by the number of trials.
- Compare that figure to your reported CAC and see whether it was in there.
- Find the single most expensive trial account last month and check what it converted to.
What trial compute costs per acquired customer
Illustrative example
A modelled 1,000 trials a month. Each trial account consumes 3,000,000 input and 240,000 output tokens over its life, priced on Claude Haiku 4.5 at real rates of $1.00 and $5.00 per million from the price book effective 2026-07-02. A modelled 8% of trials convert. Every volume and the conversion rate are modelled.
Per trial the number is $4.20 and sounds like nothing. Per acquired customer it's $52.50, because each conversion carries 12.5 trials at $4.20, its own plus the 11.5 that went nowhere. The second figure is the one that belongs beside your paid CAC, and it's usually missing from it.
Every number, with its confidence and source
| Figure | What it means | Confidence | Source |
|---|---|---|---|
| $52.50 | modelled trial compute per acquired customer, against $4.20 per trial | calculated | 1,000 modelled trials each consuming 3M input and 240k output tokens on Claude Haiku 4.5 at real rates of $1.00 and $5.00 per million from the price book effective 2026-07-02 gives $4.20 per trial and $4,200.00 a month. At a modelled 8% conversion that's 80 customers, so $4,200.00 / 80 = $52.50 each. Token volumes, trial count and conversion rate are all modelled. |
What a generic answer can’t know
On one key or project, trial spend and paid spend arrive on the same provider invoice with nothing to tell them apart. A separate trial key splits it coarsely, and past that the join is an application-level job that has to happen at capture. That's why this number is so often missing rather than wrong: nobody discarded it, it was never recorded separately. Culpa prices every call and attributes it to the account that made it, so trial accounts aggregate on their own and the distribution across them is visible while it's happening rather than afterwards. Because it also carries what each customer eventually pays, the same ledger produces the figure that closes the loop: trial compute per acquired customer, set against what that customer is worth.
Questions founders ask next
Should free trial compute count as CAC?
Yes. It's money spent to convert a prospect, which is the definition, and excluding it understates acquisition cost and overstates payback. It looks like cost of goods sold only because it arrives on the same provider invoice as paying customers' usage.
How do I calculate trial cost per acquired customer?
Total trial model spend divided by conversions, never by trials. In the modelled example $4,200.00 of monthly trial compute across 1,000 trials at 8% conversion is $52.50 per acquired customer, against $4.20 per trial. Converters carry the compute of everyone who left.
How do I stop a trial being abused?
Hard caps and per-account quotas are the blunt answer and they work. They only bind at a sensible number if you know the distribution, though, and trial usage is heavily skewed, so a limit set from the average is generous for most users and barely a limit for the tail that matters. Meter each account individually and set the cap from the tail.
Does a longer trial always cost more?
Not proportionally, because usage concentrates early for most accounts and continues only for the engaged tail. That's a distribution question rather than a duration one, and it needs per-account metering to answer for your own product rather than in general.
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Why the bill went up
Example dashboardCalls traced
418,209
across 3 projects
Spend this week
$378.41
+ $182 vs last week
Failed calls
312
74% retried, and you paid for all of them
+ $182 this week traced to one culprit
Spend over 14 days
Most expensive users
Next week forecast
Graded against reality. Accuracy shown as results land.
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Sources: Anthropic pricing. Last reviewed 2026-08-03, rates effective 2026-07-02. Plain text version.