Linkup positions itself as a straightforward search API for AI applications, with pricing that stays close to the same per-request rate whether you're making ten calls a month or ten thousand. If you're comparing it to askFinz, the useful question isn't which is simpler to price out — it's what each call actually gets you once it comes back.
What each one is
Linkup is a search API built for AI applications: send a query, get search results back, at a rate that holds roughly steady across its pricing tiers rather than dropping sharply with scale. That consistency is part of the pitch — no volume tier to plan around.
askFinz runs its own crawled web index underneath a Search workspace, a browser extension and research agents, so instead of returning results for your application to fetch and read, it returns the matched passage and an answer directly.
Side-by-side
| Dimension | Linkup | askFinz |
|---|---|---|
| Access | Search API for your own application | Search workspace, extension, and agents |
| What a call returns | Search results for your application to process | The matched passage and an answer, together |
| Rate (per 1,000 searches) | $5.00 ($0.005–0.006 per request across all tiers) | $0.75 top-up · $1.00 with the extension · $3.50 standalone |
| Pricing shape | Roughly flat per-request rate, no steep volume discount | Cheaper the more of your usage already runs through askFinz |
| Freshness | Linkup's own index, refreshed on its schedule | Continuous reading, not a scheduled rebuild |
| Content structure | Ranked results | Filed as what it is — a filing, a standard, a listing |
Linkup rate as published on its own pricing page, verified 12 August 2026 — check its current page before relying on this figure. askFinz rates are as published on pricing.
What Linkup does well
A flat, predictable per-request rate is genuinely easier to plan around than a tiered structure that requires guessing your future volume to find the real price. For a team that wants to know exactly what next month's search bill will be without modeling usage bands, Linkup's pricing is refreshingly simple, and its API is built cleanly for that straightforward use.
Where the work diverges
Linkup's flat rate covers the search call; it doesn't cover reading the page behind a result or turning that into an answer — both are still your application's job once the results land. askFinz's rate already includes the reading: the matched passage comes back with the answer, because the index has already been read rather than fetched per request. That's also the trade-off in the other direction — askFinz isn't a raw-results API you drop into your own pipeline the way Linkup is built to be.
Looking for a Linkup alternative?
If what you need is a predictable, flat-rate search call to build your own pipeline around, Linkup is a straightforward option for that. If you'd rather the reading and the answer already happened — askFinz is worth a look, inside Search and the workspaces built on it.
Which should you choose?
If you want a flat, predictable per-call rate for search results you'll process yourself, Linkup is a clean fit. If you want the answer and its source passage already assembled, at a lower rate, askFinz is the better fit.
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