Pick the Right Model for Summaries
Summarisation is the classic case where a fast, cheap model often beats a slow expensive one. You are compressing known text, not solving a novel puzzle.
Match task to model 🧠
| Task | Good model | Why |
|---|---|---|
| Short news-style recap | flash model | Fast and cheap |
| Meeting minutes with action items | standard model | Needs structure |
| Legal / financial analysis | reasoning model | High accuracy matters |
Tune the prompt first ✍️
Before upgrading models, try a sharper prompt. Specify the length, the audience and what must never be left out. A well-prompted small model often matches a lazy big one.
Measure, then decide 📏
Run your top summaries through a small scoring rubric — accuracy, completeness, style. If the small model scores well enough, keep it and bank the savings.
Frequently asked questions ❓
When should I use a reasoning model for summaries?
When the source is dense or the summary will drive decisions, like contracts, filings or medical text.
Can I mix models per document?
Yes, route by document length or difficulty — short items to flash, long complex ones to a bigger model.
How much can I save?
Teams routinely cut summarisation costs 5–10x by moving routine work to smaller models.
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