What the built-in web-search tool adds to your bill when the model browses — priced per search across OpenAI, Anthropic and Gemini.
Turning on web search adds a per-search fee and a per-search token load. For a grounded chatbot doing millions of queries, both add up fast. Cap searches per request and cache stable context. Estimate the base generation with the LLM token cost calculator and full apps on the AI agent cost calculator.
Free LLM web-search tool cost calculator — searches per request, calls per month and per-search price to the extra bill on top of tokens.
Providers bill the built-in search tool per search — commonly around $10 per 1,000 searches (roughly $0.01 each) — and that is on top of tokens. A request that fires two searches pays two tool fees plus the tokens for whatever the searches return, which is often the larger cost.
Each search injects fetched snippets or pages back into the context, and you pay input-token price to process them every time. At a few thousand tokens per search across many requests, that token cost frequently exceeds the per-search tool fee itself. Limiting searches per request and trimming returned content is the main lever.
Cost at different volumes:
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