benchmarks/web-search/multi-turn company search/for company research
45 questions · multi-hop · 16 configurations · updated 10 Sept 2026

Best web search API for company research

What the benchmark found. Parallel basic (parallel-basic) leads F1 at 46.5% across 16 configurations on 45 multi-constraint questions; 67.6s median time per task, $0.922 model cost per run. The agent is held constant, so the ranking is the search API's contribution to company research.

What this page compares. Company research with an agent means assembling facts and sets about companies from live web results, not reading a stored record. This board measures exactly that: which search API lets a fixed agent recover a complete, correct company set.

How to read it. F1 is the headline: it penalises both padding and omission. Time per task and cost per run are what a research loop pays per question. Use the lookup task on the web search hub for one-shot facts about a known company; this page is for open-ended company research.

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 →

Ranked by F1, search-only

Best web search API for company research: 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

Best web search API for company research: 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.

Common questions

What is the best web search API for company research?

Parallel basic (parallel-basic) leads F1 at 46.5% across 16 configurations on 45 multi-constraint questions; 67.6s median time per task, $0.922 model cost per run. The agent is held constant, so the ranking is the search API's contribution to company research.

Does the F1 leader also win on speed for company research?

No. Exa instant (exa-instant) has the best time per task quality at 115.0s (median time divided by F1) against 145.4s for the F1 leader Parallel basic (parallel-basic). Pick by the constraint that binds your agent.

How is company research different from one-shot lookup?

Lookup is one query, one fact, scored on answer accuracy; that board is on the web search hub. Company research here means recovering a complete company set defined by three or four constraints, which takes several searches and is scored on precision, recall and F1. The model-only baseline is 0: none of these sets is in training data.