AI Insights: Latency & Cost Optimization · part 2 of 17
rejected23 July 2026cost: included in baseline phase
Cheaper paid models: can a smaller GPT do the job?
GPT-5-mini, GPT-5-nano and older mid-tier paid models on the same task
The question
Before touching open models, can a cheaper paid tier match GPT-5.1 on this task?
rejected
Nothing cheaper on the paid side matches GPT-5.1. The mini/nano reasoning tiers add cost and delay on a short structured task.
GPT-5-mini first word22.7 sthinks before answering
GPT-5-nano first word59.8 s64 s total
Cost per answer$0.022–0.029MORE than GPT-5.1
Qualitynot bettermore text, same accuracy
Results
| Model | First word | Total time | Cost/answer | Note |
|---|---|---|---|---|
| GPT-5.1 (reference) | 1.5 s | 24 s | $0.0136 | quality bar 8.7 |
| GPT-5-mini | 22.7 s | 34.6 s | $0.022 | reasoning overhead, no quality gain |
| GPT-5-nano | 59.8 s | 64.0 s | $0.029 | worst first-word time measured |
| Older mid-tier paid models | — | — | cheaper | visibly weaker on tax content |
Why the small tiers fail here
The mini and nano tiers reason step by step before answering. For a short, structured extraction-and-advice task, that thinking phase means 8–60 seconds of dead air before the first word — the exact thing this project is trying to fix — and the extra generated text makes them cost more per answer than the bigger model they were supposed to undercut.