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Fine-tune vs Prompt

Fine-tuning is a capex-vs-opex trade: the long prompt is rent you pay on every request, and the tuning run is a one-off purchase that deletes those tokens. Volume decides which wins — at low volume the payback never arrives, at high volume it arrives embarrassingly fast. Put in your prompt overhead and your tuning quote; the payback line tells you which regime you are in.

The prompt path

The tuned path

Use your provider's current price sheet and a real tuning quote — prices move; this calculator never assumes them for you.

Prompt overhead per day

$45.00

Tuned overhead per day

$0.00

Daily savings

$45.00

Tuning cost paid back in

11.1 days

Repaid at $45 of savings a day; every request after that is margin.

First-year net

$15,925.00

365 days of savings minus the one-off tuning cost.

Fine-tuning is capex: you pay once to delete tokens the prompt pays for on every request, so volume decides everything — at a few hundred requests a day the payback sits years out, past the model's useful life; at real volume it lands in days. One honest simplification: this compares the removable tokens only. A provider premium on tuned models applies to every token of every request, so if yours charges one, the true tuned cost is higher than shown.

How to read it: compare the payback period to the model's useful life, not to zero — a payback that lands after the base model is deprecated never really lands, and every base-model upgrade means paying the tuning cost again. The comparison covers the removable prompt tokens only: if your provider prices tuned-model tokens at a premium, that premium applies to your whole bill, not just these tokens, and can wipe out the savings. And try prompt caching first — it is the cheaper way to buy back the same tokens; rerun this after caching and see if the trade still clears.

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