Most Accurate News API for LLMs, 2026
Most Accurate News API for LLMs: Exa fast leads 15 news and search APIs at 99.3% accuracy on 300 company-news questions, independently benchmarked in 2026.
What this page compares. This page ranks measured results from company-news factual lookup (web search APIs and news indexes).
How to read the result. The table ranks every complete run by its score on the same questions. Latency and cost are shown beside it and not blended into the score.
Company-news factual lookup, web search APIs and news indexes, ranked by accuracy
Every row ran the same 300 questions. Provider names link to the official docs for the configuration measured.
| Rank | Provider | Type | Accuracy | Answer recall @5 | Median search time | $ / 1k queries | $ / 1k correct | Result tokens | Accuracy / 1k tokens | List price |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Exa fasttype=fast | Web search | 99.3% | 99.3% | 569 ms | $7.00 | $7.05 | 1,987 | 50.0 | $7.00 / 1k queries |
| 2 | Exa instanttype=instant | Web search | 97.7% | 97.3% | 386 ms | $7.00 | $7.17 | 2,128 | 45.9 | $7.00 / 1k queries |
| 3 | Perplexity lowsearch_context_size=low | Web search | 97.3% | 98.3% | 1.6 s | $5.00 | $5.14 | 476 | 205 | $5.00 / 1k queries |
| 4 | Linkup fastdepth=fast · outputType=searchResults | Web search | 96.7% | 94.7% | 1.2 s | $5.00 | $5.17 | 3,022 | 32.0 | $5.00 / 1k queries |
| 5 | SERPlimit=10 | Web search | 96.0% | 95.0% | 578 ms | $3.00 | $3.13 | 497 | 193 | $3.00 / 1k queries |
| 6 | Firecrawlfirecrawl-search | Web search | 95.3% | 96.7% | 471 ms | $5.00 | $5.24 | 678 | 141 | $5.00 / 1k queries |
| 7 | Brave Search llm-contextcount=10 | Web search | 94.0% | 94.7% | 590 ms | $5.00 | $5.32 | 2,064 | 45.6 | $5.00 / 1k queries |
| 8 | Brave Search webcount=10 · result_filter=web | Web search | 93.3% | 91.7% | 613 ms | $5.00 | $5.36 | 817 | 114 | $5.00 / 1k queries |
| 9 | Parallel basicmode=basic | Web search | 93.3% | 92.0% | 1.8 s | $5.00 | $5.36 | 2,330 | 40.1 | $5.00 / 1k queries |
| 10 | Nimble standardsearch_depth=standard · full_content=false · focus=general | Web search | 93.0% | 94.3% | 822 ms | $5.00 | $5.38 | 2,730 | 34.1 | $5.00 / 1k queries |
| 11 | Tavily advancedsearch_depth=advanced | Web search | 93.0% | 92.7% | 4.2 s | $16.00 | $17.20 | 2,210 | 42.1 | $16.00 / 1k queries |
| 12 | Linkup standarddepth=standard · outputType=searchResults | Web search | 92.0% | 90.3% | 2.1 s | $5.00 | $5.43 | 2,983 | 30.8 | $5.00 / 1k queries |
| 13 | TinyFishfree · 30 req/min cap | Web search | 92.0% | 90.7% | 2.3 s | $0 | $0 | 441 | 208 | $0 / 1k queries |
| 14 | You highlights coreextraction_mode=highlights · knowledge=core | Web search | 92.0% | 89.7% | 815 ms | $5.00 | $5.43 | 2,862 | 32.1 | $5.00 / 1k queries |
| 15 | You highlightsextraction_mode=highlights | Web search | 90.7% | 89.7% | 614 ms | $5.00 | $5.51 | 2,837 | 32.0 | $5.00 / 1k queries |
| 16 | Tavily basicsearch_depth=basic | Web search | 87.7% | 87.7% | 1.7 s | $8.00 | $9.13 | 1,639 | 53.5 | $8.00 / 1k queries |
| 17 | Parallel fastmode=fast | Web search | 86.0% | 79.0% | 861 ms | $1.00 | $1.16 | 1,839 | 46.8 | $1.00 / 1k queries |
| 18 | Nimble litesearch_depth=lite · full_content=false · focus=general | Web search | 75.3% | 75.3% | 1.4 s | $1.10 | $1.46 | 413 | 183 | $1.10 / 1k queries |
| 19 | Parallel turbomode=turbo | Web search | 71.3% | 66.0% | 315 ms | $1.00 | $1.40 | 1,853 | 38.5 | $1.00 / 1k queries |
| 20 | Seltz newsscope=news | News index | 58.3% | 60.0% | 386 ms | $5.00 | $8.57 | 2,919 | 20.0 | $5.00 / 1k queries |
| 21 | Autobound news eventsdomain · signal_types=news · signal_subtypes · limit=10 | News index | 30.0% | 25.0% | 160 ms | $36.23 | $120.76 | 879 | 34.1 | $9.50 / 1k credits |
| 22 | PredictLeads news_eventsLLM category pick · categories[] · limit=10 | News index | 20.7% | 20.0% | 376 ms | $40.00 | $193.52 | 484 | 42.7 | $40.00 / 1k queries |
| 23 | Datahyena company eventsdomain · include=funding|acquisitions|exec_moves | News index | 5.3% | 6.7% | 245 ms | $38.17 | $716.07 | 22 | 238 | $50.00 / 1k credits |
How the ranking was measured
- Every API received the same natural-language question about a recent company event, one search per question, up to 10 results.
- Each answer is a single verifiable value pinned to an official wire or newsroom URL, fixed before any vendor ran.
- Accuracy is whether the returned results let the same answering model extract the correct value.
- Latency is the search request time. Cost is the recorded list price for the calls made, per 1,000 queries and per 1,000 correct answers.
- The runner and published data are open in openbenchmarks-labs/company-news ↗ and openbenchmarks/OB-News-Websearch ↗. The full methodology is on the Company News Search Benchmark →
Questions answered by this comparison
Which provider leads most Accurate News API for LLMs?
Exa fast leads this table at 99.3% accuracy, on 300 company-news questions.
How was this measured?
Every API received the same natural-language question about a recent company event, one search per question, up to 10 results. Each answer is a single verifiable value pinned to an official wire or newsroom URL, fixed before any vendor ran. Accuracy is whether the returned results let the same answering model extract the correct value. Latency is the search request time. Cost is the recorded list price for the calls made, per 1,000 queries and per 1,000 correct answers.
How should speed and cost be read beside the score?
Exa fast recorded 569 ms median search time and $7.00 per 1,000 queries. The most accurate configuration is rarely the fastest or the cheapest, so each is reported in its own column.
Do vendors pay to be ranked?
No. Inclusion and rank do not depend on vendor payments. Every API used the same questions, answering model and scoring.
What does this page not test?
This page ranks measured results from company-news factual lookup (web search APIs and news indexes).