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Vector runs on your own AI key, so every research run, comparison and monitoring check is billed to you by your provider, not by Vector. That makes one question practical: what did this actually cost? Open Settings and go to the AI Usage tab. Token usage & cost is the whole record.
The AI Usage tab in Settings, showing total cost tiles above a log of individual AI calls with model, tokens and cost

Token usage & cost: the running totals, and a line for every AI call

See what you’ve spent

The tiles across the top add up the whole log:
  • Total cost, and AI cost — the part spent on AI rather than fetching pages
  • AI calls, input and output tokens, and prompt-cache tokens written and read
  • Web searches and page Fetches
  • Web scrapers — how many paid fetches the web scrapers made, and what they cost

Find out who spent it

Who spent it splits the last 30 days of spend in two:
  • Automatic (scheduled) — runs nobody started by hand: the monitoring schedule, and the checks it catches up on after downtime.
  • You & your team — everything started by a person.
Each side shows its cost, how many calls it made, and the features that spent the most. If the automatic side is higher than you’d like, check the competitors you watch least closely less often.

See what a single call cost

Below the totals, the log has a line for each of the most recent 100 AI calls: When, the Feature that made it — competitor search, product description, a pricing scan — the Model that ran it, tokens in and out, cache reads and writes, web searches, and its cost. Fetches by a web scraper appear in the same log, so fetching a page and reasoning about it read side by side.

Check whether a cheaper model saves money

Because every line names its model and feature, the log is how you measure routing: move a heavy function to a cheaper model, and that feature’s lines get cheaper from its next run.

How a call’s cost is worked out

A call’s cost is its real cost, priced at the rate of the model and provider that actually ran it: input tokens, output tokens, prompt-cache writes and reads, plus the provider’s fee when the call used web search. Token and cache prices come from Vector’s AI models dataset, so the figures track what providers actually charge. The log is a record after the fact: Vector doesn’t cap spending or alert you when it grows.

Keep spend separate per company

Each workspace has its own key and its own record. Work in one company’s workspace is never billed to another’s key. Guests can’t spend your budget at all: AI actions are blocked for them before any provider is called. See Members and roles.

Clear the log

Clear usage log empties the record, after asking you to confirm. It’s a log of what happened, not a bill: clearing it changes nothing about what your provider charges you.

Where to go next

Choose a model per function

The main lever on what you spend.

Connect web scrapers

The other cost recorded here.