Skip to main content
A model only knows what it was trained on. Turn on web search and it can look things up first — then the answer arrives with the pages it used attached, so you can check it rather than trust it.
A chat answer about subtitle timing, citing a streaming platform's style guide. Above the bubble a badge reads Searched the web, Brave, 2 sources, plus 2 credits. A superscript 1 sits inside the text on the sentence that states the platform's character-per-second cap, and below the bubble a panel headed 2 SOURCES, BRAVE lists two pages from the same partner help center, each with its title and domain.

A web-search answer: the badge above it names the provider and the cost, and the sources are listed underneath. Plain prose like this also gets an inline superscript on the grounded sentence — most real answers use enough markdown that the marker doesn't appear, but the sources panel always does.

Turning it on

The globe in the message bar toggles search for the chat, not for one message — once on, every following message can search. The dropdown beside it picks where the searching happens. Auto resolves by the model’s name: gpt-* and o* to OpenAI, gemini-* to Gemini, claude-* to Anthropic. A model in none of those families — Llama, Qwen, Mistral, DeepSeek, Grok — has no grounding of its own, so Auto uses Brave. Hovering the globe tells you which one Auto has landed on for the model you have selected. That is the practical difference between the two kinds. Grounded search is the model searching for itself, and it is only available on the family that built it. Brave is search bolted on from outside, which makes it the only option that works everywhere: it will give an open-weights model access to the live web that the model has no native way to reach.
The setting is saved on the chat, so a thread you left with search on still has it on when you come back — and switching the model inside that chat does not turn it off. New chats start with it off.

Reading the result

Two things always appear on an answer that searched, and a third — the inline marker below — appears when the answer’s formatting allows it. The badge, above the bubble: which provider ran, how many sources came back, and what the search added to the bill. It reads Searched the web · Brave · 2 sources · +0.25 cr. Inline citations — a small superscript number inside the text, on the claim it belongs to, when the renderer can place one. Click one to see the source it points at, and the quoted passage where the provider gave one. The marker is best-effort, not guaranteed: it only appears on a plain-prose answer with no markdown in it, because injecting a citation chip into a heading, list, code block or link would break the formatting around it. A real model answer very often does use markdown, and the moment it does, the marker is simply not rendered — the sources panel below is unaffected either way, so the citations themselves are never lost, only the in-text pointer to them. The sources panel, under the answer: every page, numbered to match the superscripts, with its title and domain. Click through to the original.

”no sources”

A badge can say no sources instead of a count. That is not a rendering problem — it means the provider ran a search, billed for it, and attributed nothing to it. It is shown rather than hidden precisely because the search was still paid for.

What it costs

Search is billed on top of the message, and the badge on each answer shows what that message’s search actually added. The two kinds cost differently:
  • Brave charges per search request, and nothing else. The model then reads the results as ordinary input.
  • Grounded providers charge a per-search fee plus the tokens their grounding machinery consumed — which is why the same question can cost more through a grounded provider than through Brave, on the same model.
A single message can run more than one search when the model decides it needs to; the badge reports the total, so what you are billed is always what is on the screen.

When to use which

  • Anything current — prices, releases, versions, “what changed” — needs search regardless of the model. Training cutoffs are the whole reason this feature exists.
  • On an open-weights model, Brave is the only way to reach the live web.
  • On a frontier model, its own grounding usually reads the page more carefully than a result snippet does, and costs a little more for it.
  • Leave it off for reasoning, writing, and code that does not depend on anything outside the conversation. A search you did not need is a search you paid for.

In workflows

The same providers are available as a Web search step, where the results are structured output you can route into later steps rather than prose in a chat. See Step types.