Live Web Search Benchmarks: Pick the Right Engine, Depth, and Model for Your Agent

OpenRouter’s live web-search benchmarks compare models, search engines, search methods, and search budgets across fact-finding, multi-hop research, broad collection, and expert-question workloads to help users select configurations for their agents. Results indicate that increasing the allowed number of search turns often produces the largest quality gains, sometimes roughly doubling performance from one to 25 turns, though deeper searches can add unnecessary cost on simpler tasks and may be especially costly when models repeatedly search without finding an answer. Model choice generally has a greater effect on performance than engine choice, while engine selection can still meaningfully affect quality, cost, and latency depending on the task and model. The benchmarks distinguish a fast single-search web plugin from a server tool that allows iterative model-directed searching, and recommend testing the most promising low-cost configurations against an organization’s own evaluation set. Benchmark runs use production APIs and standardized conditions, including search-result excerpts without page fetching or code execution, while live leaderboards are updated as new qualifying runs are completed.

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