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

Seltz for research agents: multi-hop company search, measured

What the benchmark found. Seltz (seltz-companies) ranks 15 of 16 search-only configurations at 14.5% F1 (precision 40.0%, recall 9.4%), -32.0 pp versus the leader, Parallel basic (parallel-basic) at 46.5%. Median time per task 55.2s, model cost per run $1.446.

What this page compares. Seltz is a companies-scope answer API. This page isolates its rows on the multi-turn company search board so its numbers can be read against the leader and against every other web search API on the same 45 questions.

How to read it. Rank and F1 are the headline; precision and recall show whether misses come from padding or omission. Time per task and cost per run are what an agent loop actually pays. Search-only and search + fetch are separate boards because page fetching changes the ranking for some providers and not others.

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

Seltz for research agents: multi-hop company search, measured: 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

Seltz for research agents: multi-hop company search, measured: 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

Is Seltz a good web search API for research agents?

Seltz (seltz-companies) ranks 15 of 16 search-only configurations at 14.5% F1 (precision 40.0%, recall 9.4%), -32.0 pp versus the leader, Parallel basic (parallel-basic) at 46.5%. Median time per task 55.2s, model cost per run $1.446.

Does page fetching help Seltz on multi-hop search?

Seltz (seltz-companies) scores 16.3% F1 with search + fetch versus 14.5% search-only, a change of +1.7 pp. Fetch adds latency and model tokens on every run, so it pays only when the snippet alone cannot verify a constraint.

How does Seltz compare with the board leader?

Parallel basic (parallel-basic) leads at 46.5% F1, 67.6s median time per task and $0.922 model cost per run; Seltz (seltz-companies) is at 14.5%, 55.2s and $1.446. Time per task quality (median time divided by F1): 145.4s versus 379.7s.