Best API for GTM List Building 2026: Similar Companies or Build a List
Independent 2026 benchmark (open source code, open data): best API for GTM list building, ranked two ways. Seltz on similar companies; Parallel basic on building a list.
GTM list building starts with the search input. Either you have seed accounts and want similar companies, or you build a list from a description (industry, stage, city, hiring). Those are different APIs and different rankings. This page has both, live. Filter UIs are a third input and are not scored here.
Best API for GTM list building, by input
There is no single best API across both jobs. Read the ranking that matches how you will query.
- Similar companies, long list: Seltz: 63.4% Precision@100 across 48 seed companies.
- Similar companies, short list: PredictLeads: 89.8% Precision@10.
- Build a list, search-only: Parallel basic: 46.5% F1 on 45 multi-constraint company searches. Snippets, no fetch.
- Build a list, search & fetch: Exa deep: 48.2% F1. Agent opens pages.
Search by similar companies
One seed company in. A list of lookalikes out. Same seeds, same judge panel. Precision@10 is the shortlist a rep works by hand. Precision@100 is the long list that feeds a sequence.
Build a list
Describe the companies you want in plain language, with three or four constraints. The agent has to return the complete set. Ranked on F1. Search-only and search & fetch stay separate. Model-only baseline is 0.
Web Search only
| Provider | Endpoint & configuration | F1 | Precision | Recall | Exact set |
|---|---|---|---|---|---|
| Parallel | POST /v1/search mode=basicparallel-basic | 46.5 ± 1.9 | 88.7 ± 0.9 | 34.4 ± 2.0 | 3.7 ± 2.6 |
| Exa | POST /search type=deepexa-deep | 45.4 ± 2.0 | 83.2 ± 3.0 | 33.7 ± 1.4 | 1.5 ± 1.3 |
| Parallel | POST /v1/search mode=advancedparallel-advanced | 44.2 ± 1.4 | 87.6 ± 3.4 | 32.0 ± 1.6 | 2.2 ± 0.0 |
| Exa | POST /search type=instantexa-instant | 43.3 ± 1.0 | 82.6 ± 3.8 | 32.2 ± 0.5 | 3.0 ± 1.3 |
| Linkup | POST /v1/search depth=fastlinkup-fast | 41.1 ± 1.7 | 82.8 ± 1.0 | 30.3 ± 1.5 | 0.7 ± 1.3 |
| Tavily | POST /search search_depth=advancedtavily-advanced | 41.1 ± 2.3 | 83.7 ± 4.2 | 29.8 ± 1.7 | 2.2 ± 0.0 |
| Linkup | POST /v1/search depth=standardlinkup-standard | 40.6 ± 0.9 | 84.0 ± 7.9 | 29.7 ± 1.4 | 1.5 ± 2.6 |
| Parallel | POST /v1/search mode=fastparallel-fast | 38.0 ± 2.0 | 79.9 ± 4.6 | 27.5 ± 1.4 | 1.5 ± 1.3 |
| Perplexity | POST /searchsearch_context_size=low | 37.8 ± 2.1 | 79.3 ± 5.7 | 26.8 ± 1.4 | 2.2 ± 2.2 |
| Parallel | POST /v1/search mode=turboparallel-turbo | 34.7 ± 2.4 | 80.0 ± 5.2 | 24.8 ± 2.4 | 1.5 ± 1.3 |
| You | POST /v1/searchyou | 33.1 ± 2.4 | 75.7 ± 3.1 | 23.1 ± 1.9 | 1.5 ± 1.3 |
| Firecrawl | POST /v2/searchfirecrawl | 30.4 ± 1.1 | 77.3 ± 4.4 | 20.7 ± 0.7 | 2.2 ± 0.0 |
| Brave Search | GET /res/v1/web/searchbrave | 28.0 ± 1.7 | 66.9 ± 8.5 | 19.3 ± 0.5 | 0.7 ± 1.3 |
| TinyFish | GET api.search.tinyfish.aitinyfish | 26.6 ± 1.3 | 64.7 ± 1.5 | 17.9 ± 0.8 | 1.5 ± 1.3 |
| Seltz | POST /v1/search scope=companiesseltz-companies | 14.5 ± 0.9 | 40.0 ± 3.1 | 9.4 ± 0.7 | 0.0 ± 0.0 |
| SERP (RapidAPI) | GET google-search74.p.rapidapi.comserp | 0.4 ± 0.6 | 0.7 ± 1.3 | 0.3 ± 0.4 | 0.0 ± 0.0 |
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.
Web Search + Fetch
| Provider | Endpoint & configuration | F1 | Precision | Recall | Exact set |
|---|---|---|---|---|---|
| Exa | POST /search type=deepexa-deep | 48.2 ± 2.1 | 89.4 ± 1.2 | 36.0 ± 2.2 | 2.2 ± 2.2 |
| Perplexity | POST /searchsearch_context_size=high | 46.6 ± 2.0 | 87.7 ± 5.9 | 34.7 ± 1.1 | 2.2 ± 2.2 |
| Exa | POST /search type=instantexa-instant | 44.9 ± 0.9 | 85.9 ± 2.5 | 33.5 ± 0.9 | 5.2 ± 1.3 |
| Parallel | POST /v1/search mode=basicparallel-basic | 42.3 ± 1.1 | 81.3 ± 2.8 | 31.3 ± 1.1 | 3.0 ± 1.3 |
| Parallel | POST /v1/search mode=advancedparallel-advanced | 42.2 ± 1.1 | 87.6 ± 0.3 | 30.1 ± 1.1 | 2.2 ± 0.0 |
| Linkup | POST /v1/search depth=standardlinkup-standard | 42.0 ± 1.8 | 90.7 ± 2.0 | 30.5 ± 2.0 | 3.0 ± 3.4 |
| Tavily | POST /search search_depth=advancedtavily-advanced | 41.0 ± 1.3 | 89.4 ± 6.0 | 29.1 ± 0.7 | 2.2 ± 0.0 |
| Linkup | POST /v1/search depth=fastlinkup-fast | 39.9 ± 1.3 | 85.3 ± 3.6 | 28.6 ± 1.3 | 0.7 ± 1.3 |
| Parallel | POST /v1/search mode=fastparallel-fast | 39.3 ± 3.3 | 82.3 ± 6.6 | 28.2 ± 2.0 | 2.2 ± 0.0 |
| Parallel | POST /v1/search mode=turboparallel-turbo | 36.0 ± 3.5 | 83.6 ± 4.0 | 25.0 ± 2.6 | 0.0 ± 0.0 |
| You | POST /v1/searchyou | 34.0 ± 0.9 | 78.8 ± 0.6 | 23.8 ± 1.2 | 3.0 ± 1.3 |
| Firecrawl | POST /v2/searchfirecrawl | 33.2 ± 2.1 | 83.3 ± 0.8 | 22.7 ± 1.8 | 1.5 ± 1.3 |
| TinyFish | GET api.search.tinyfish.aitinyfish | 30.2 ± 3.5 | 70.9 ± 11.3 | 20.9 ± 2.5 | 0.0 ± 0.0 |
| Brave Search | GET /res/v1/web/searchbrave | 29.4 ± 1.6 | 73.5 ± 5.8 | 20.4 ± 0.9 | 1.5 ± 1.3 |
| Seltz | POST /v1/search scope=companiesseltz-companies | 16.3 ± 1.5 | 49.5 ± 2.4 | 10.2 ± 1.2 | 0.0 ± 0.0 |
| SERP (RapidAPI) | GET google-search74.p.rapidapi.comserp | 0.0 ± 0.0 | 0.0 ± 0.0 | 0.0 ± 0.0 | 0.0 ± 0.0 |
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.
Best API for GTM list building: FAQ
What is the best API for GTM list building in 2026?
Pick by input. Similar companies (a seed account in, lookalikes out) is ranked on Precision@100 / Precision@10. Seltz leads the long list at 63.4% Precision@100. PredictLeads leads the short list at 89.8% Precision@10. Build a list (describe the ICP, get a company set) is ranked on F1. Search-only leader: Parallel basic at 46.5% F1. Search & fetch leader: Exa deep at 48.2% F1. Those two jobs do not share a winner.
What is the best API to make company lists?
Same split. If the list is companies like these, use the lookalike ranking. If you are building a list from a brief (industry, stage, geography, hiring), use the company-search ranking. Filter UIs in ZoomInfo, Apollo, or Clay are a third input and are not scored on either table.
What is the best web search API for company search?
That job is Build a list on this page: 45 questions with three or four constraints, scored on F1 against a human-reviewed gold set. Search-only: Parallel basic at 46.5% F1. Search & fetch: Exa deep at 48.2% F1. It is not a lookalike API and not a one-shot news lookup. Full method: multi-turn company search.
What is the best API for GTM prospecting?
Prospecting here means account discovery, not contact finders or sequencing. Similar companies and Build a list are the two measured discovery APIs on this page. Enrichment, funding data, and work-email APIs are later pipeline steps and have their own rankings.
Is there a best API for GTM overall?
No. GTM is a stack. This page ranks list building (finding the accounts). It does not rank enrichment, intent, or outbound. Do not average the two tables on this page into one GTM winner.
How is similar companies different from Build a list?
Similar companies: one seed domain in, a ranked list of lookalikes out, scored on whether a judge panel finds those companies relevant. Build a list: a multi-part description in, a complete company set out, scored on precision, recall, and F1 against gold. A vendor that leads one job can lose the other.
Is this independent, with open source code and open data?
Yes. No vendor pays for inclusion or rank. Lookalikes: identical seeds, public request/response and judge prompts (https://github.com/openbenchmarks-labs/lookalikes). Build a list: question, prompt, model, and budgets held constant (https://github.com/openbenchmarks-labs/multi-turn-company-search; dataset https://huggingface.co/datasets/openbenchmarks/OB-Company-Websearch).