benchmarks/web-search/multi-turn company search/browsecomp vs livebrowsecomp
45 questions · multi-hop · 16 configurations · updated 10 Sept 2026

BrowseComp vs LiveBrowseComp vs multi-turn company search

What the benchmark found. Current output of the method: Parallel basic (parallel-basic) leads F1 at 46.5% across 16 configurations on 45 questions.

What this page compares. Six fanouts in the probe searched for LiveBrowseComp and landed on arXiv. This page places the three benchmarks side by side: what is held constant, what is scored, and what training-data contamination does to each.

How to read it. BrowseComp and LiveBrowseComp evaluate agents; this benchmark evaluates search APIs with the agent held constant. They answer different questions and are not competing leaderboards.

Method in one paragraph. The same agent, prompt, turn budget and tool schema run against every web search API on 45 questions that each define a company set by three or four constraints. Every returned company is resolved to a canonical identity and compared with a human-reviewed gold set; precision, recall, F1 and exact-set are averaged over three runs per question. The model-only baseline is 0.

Most accurate · Fastest · Cheapest · Find companies by criteria · Search + fetch · Full benchmark

open runner + judgePublic in openbenchmarks-labs/multi-turn-company-search; dataset openbenchmarks/OB-Company-Websearch.github →

What each term means here

Why not just run BrowseComp against each search API?

Because agents answer up to 44.5% of BrowseComp with no search tool at all (LiveBrowseComp, Fan et al., 2026). A benchmark the model can partly answer from memory cannot isolate the search API's contribution.

Is LiveBrowseComp a substitute?

It fixes contamination by using fresh facts, but it still evaluates the browsing agent end to end. To compare search APIs you also need the agent fixed and the questions built so the model-only baseline is zero, which is what this board does.

Can I compare scores across the three?

No. Different tasks, different scoring, different units. Use BrowseComp-style sets to compare agents and this board to compare the search API behind one agent.

Ranked by F1, search-only

BrowseComp vs LiveBrowseComp vs multi-turn company search: search-only
ProviderEndpoint & configurationF1PrecisionRecallExact setMedian timeMean turnsMedian task costAPI list price
ParallelPOST /v1/search mode=basicparallel-basic46.5 ± 1.988.7 ± 0.934.4 ± 2.03.7 ± 2.667.6 s7.4$1.120$0.070 search$1.050 token cost$0.005 / search
ExaPOST /search type=deepexa-deep45.4 ± 2.083.2 ± 3.033.7 ± 1.41.5 ± 1.389.5 s7.4$0.717$0.156 search$0.556 token cost$0.012 / search
ParallelPOST /v1/search mode=advancedparallel-advanced44.2 ± 1.487.6 ± 3.432.0 ± 1.62.2 ± 0.083.4 s7.3$0.625$0.070 search$0.565 token cost$0.005 / search
ExaPOST /search type=instantexa-instant43.3 ± 1.082.6 ± 3.832.2 ± 0.53.0 ± 1.349.8 s7.3$0.652$0.091 search$0.559 token cost$0.007 / search
LinkupPOST /v1/search depth=fastlinkup-fast41.1 ± 1.782.8 ± 1.030.3 ± 1.50.7 ± 1.364.2 s7.4$0.923$0.070 search$0.853 token cost$0.005 / search
TavilyPOST /search search_depth=advancedtavily-advanced41.1 ± 2.383.7 ± 4.229.8 ± 1.72.2 ± 0.092.2 s7.4$1.029$0.224 search$0.808 token cost$0.016 / search
LinkupPOST /v1/search depth=standardlinkup-standard40.6 ± 0.984.0 ± 7.929.7 ± 1.41.5 ± 2.672.3 s7.3$0.937$0.070 search$0.867 token cost$0.005 / search
ParallelPOST /v1/search mode=fastparallel-fast38.0 ± 2.079.9 ± 4.627.5 ± 1.41.5 ± 1.353.9 s7.6$0.460$0.014 search$0.447 token cost$0.001 / search
PerplexityPOST /searchsearch_context_size=low37.8 ± 2.179.3 ± 5.726.8 ± 1.42.2 ± 2.248.9 s7.7$0.334$0.070 search$0.264 token cost$0.005 / search
ParallelPOST /v1/search mode=turboparallel-turbo34.7 ± 2.480.0 ± 5.224.8 ± 2.41.5 ± 1.346.4 s7.6$0.419$0.014 search$0.405 token cost$0.001 / search
YouPOST /v1/searchyou33.1 ± 2.475.7 ± 3.123.1 ± 1.91.5 ± 1.346.2 s7.7$0.477$0.070 search$0.408 token cost$0.005 / search
FirecrawlPOST /v2/searchfirecrawl30.4 ± 1.177.3 ± 4.420.7 ± 0.72.2 ± 0.075.0 s7.9$0.282$0.070 search$0.212 token cost$0.005 / search
Brave SearchGET /res/v1/web/searchbrave28.0 ± 1.766.9 ± 8.519.3 ± 0.50.7 ± 1.343.5 s8.0$0.268$0.070 search$0.200 token cost$0.005 / search
TinyFishGET api.search.tinyfish.aitinyfish26.6 ± 1.364.7 ± 1.517.9 ± 0.81.5 ± 1.364.2 s7.9$0.212$0.000 search$0.212 token cost$0 / search
SeltzPOST /v1/search scope=companiesseltz-companies14.5 ± 0.940.0 ± 3.19.4 ± 0.70.0 ± 0.055.2 s7.3$1.751$0.070 search$1.681 token cost$0.005 / search
SERP (RapidAPI)GET google-search74.p.rapidapi.comserp0.4 ± 0.60.7 ± 1.30.3 ± 0.40.0 ± 0.031.4 s7.8$0.103$0.036 search$0.065 token cost$0.003 / search

F1, precision, recall, and exact-set accuracy are percentages reported as mean ± sample SD across three independent runs; each run aggregates all 45 questions. SD is measured in percentage points. Median time is the median end-to-end time across all runs for each vendor. Median task cost is the median of LLM $ plus search/fetch API $ per agent run. API list price is the PAYG unit rate of the search (and fetch) endpoint the harness calls.

Same sort, with a page-reading tool enabled

BrowseComp vs LiveBrowseComp vs multi-turn company search: search + fetch
ProviderEndpoint & configurationF1PrecisionRecallExact setMedian timeMean turnsMedian task costAPI list price
ExaPOST /search type=deepexa-deep48.2 ± 2.189.4 ± 1.236.0 ± 2.22.2 ± 2.295.8 s7.5$0.683$0.156 search+fetch$0.526 token cost$0.012 / search$0.001 / fetch
PerplexityPOST /searchsearch_context_size=high46.6 ± 2.087.7 ± 5.934.7 ± 1.12.2 ± 2.253.9 s7.5$0.504$0.070 search+fetch$0.441 token cost$0.005 / search
ExaPOST /search type=instantexa-instant44.9 ± 0.985.9 ± 2.533.5 ± 0.95.2 ± 1.352.5 s7.5$0.653$0.091 search+fetch$0.557 token cost$0.007 / search$0.001 / fetch
ParallelPOST /v1/search mode=basicparallel-basic42.3 ± 1.181.3 ± 2.831.3 ± 1.13.0 ± 1.368.6 s7.5$1.089$0.061 search+fetch$1.033 token cost$0.005 / search$0.001 / fetch
ParallelPOST /v1/search mode=advancedparallel-advanced42.2 ± 1.187.6 ± 0.330.1 ± 1.12.2 ± 0.080.9 s7.4$0.599$0.061 search+fetch$0.538 token cost$0.005 / search$0.001 / fetch
LinkupPOST /v1/search depth=standardlinkup-standard42.0 ± 1.890.7 ± 2.030.5 ± 2.03.0 ± 3.481.0 s7.5$0.911$0.070 search+fetch$0.848 token cost$0.005 / search$0.001 / fetch
TavilyPOST /search search_depth=advancedtavily-advanced41.0 ± 1.389.4 ± 6.029.1 ± 0.72.2 ± 0.092.6 s7.3$0.898$0.195 search+fetch$0.685 token cost$0.016 / search$0.0032 / fetch
LinkupPOST /v1/search depth=fastlinkup-fast39.9 ± 1.385.3 ± 3.628.6 ± 1.30.7 ± 1.368.0 s7.3$0.903$0.061 search+fetch$0.837 token cost$0.005 / search$0.001 / fetch
ParallelPOST /v1/search mode=fastparallel-fast39.3 ± 3.382.3 ± 6.628.2 ± 2.02.2 ± 0.055.1 s7.6$0.441$0.014 search+fetch$0.427 token cost$0.001 / search$0.001 / fetch
ParallelPOST /v1/search mode=turboparallel-turbo36.0 ± 3.583.6 ± 4.025.0 ± 2.60.0 ± 0.048.1 s7.7$0.414$0.013 search+fetch$0.400 token cost$0.001 / search$0.001 / fetch
YouPOST /v1/searchyou34.0 ± 0.978.8 ± 0.623.8 ± 1.23.0 ± 1.347.4 s7.8$0.489$0.065 search+fetch$0.427 token cost$0.005 / search$0.001 / fetch
FirecrawlPOST /v2/searchfirecrawl33.2 ± 2.183.3 ± 0.822.7 ± 1.81.5 ± 1.382.1 s7.9$0.295$0.063 search+fetch$0.230 token cost$0.005 / search$0.0025 / fetch
TinyFishGET api.search.tinyfish.aitinyfish30.2 ± 3.570.9 ± 11.320.9 ± 2.50.0 ± 0.063.4 s7.9$0.219$0.000 search+fetch$0.219 token cost$0 / search$0 / fetch
Brave SearchGET /res/v1/web/searchbrave29.4 ± 1.673.5 ± 5.820.4 ± 0.91.5 ± 1.345.1 s8.0$0.285$0.060 search+fetch$0.222 token cost$0.005 / search
SeltzPOST /v1/search scope=companiesseltz-companies16.3 ± 1.549.5 ± 2.410.2 ± 1.20.0 ± 0.060.1 s7.5$1.741$0.070 search+fetch$1.671 token cost$0.005 / search
SERP (RapidAPI)GET google-search74.p.rapidapi.comserp0.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.033.4 s7.8$0.102$0.039 search+fetch$0.066 token cost$0.003 / search

F1, precision, recall, and exact-set accuracy are percentages reported as mean ± sample SD across three independent runs; each run aggregates all 45 questions. SD is measured in percentage points. Median time is the median end-to-end time across all runs for each vendor. Median task cost is the median of LLM $ plus search/fetch API $ per agent run. API list price is the PAYG unit rate of the search (and fetch) endpoint the harness calls.