Automate in-depth web research with structured output support.
instructions
are parsed by an LLM that decomposes the task into one or more research steps.
outputSchema
) or a detailed markdown report.
researchId
. You can poll the request until it is complete or failed, or list all tasks to monitor progress in bulk.
Model | p50 (seconds) | p90 (seconds) |
---|---|---|
exa-research | 45 | 90 |
exa-research-pro | 90 | 180 |
Operation | exa-research | exa-research-pro | Notes |
---|---|---|---|
Search | $5/1k searches | $5/1k searches | Each unique search query issued by the agent |
Page read | $5/1k pages read | $10/1k pages read | One “page” = 1,000 tokens from the web |
Reasoning tokens | $5/1M tokens | $5/1M tokens | Specific LLM tokens used for reasoning and synthesis |
exa-research
that performs 6 searches, reads 20 pages of content, and uses 1,000 reasoning tokens would cost:
For exa-research-pro
, the same task would cost:
Who is the Research API for?
How is this different from the /answer endpoint?
/answer
is designed for single-shot Q&A. The Research API handles
long-running, multi-step investigations. It’s suitable for tasks that
require complex reasoning over web data.How long do tasks take?
What are best practices for writing instructions?
How large can my output schema be?
What happens if my schema validation fails?