Tavily vs Firecrawl
Tavily versus Firecrawl for AI agents — hit@k accuracy, freshness lag, cost per verified-correct answer, and agent-readiness, scored against golden truth.
On the illustrative web_search-2026-q3 snapshot, Tavily wins more head-to-head metrics (6 of 6). Tavily leads on accuracy; compare cost per verified-correct answer and freshness below.
Head to Head — Web Search
| Metric | Tavily | Firecrawl | Winner |
|---|---|---|---|
| hit@1 % | 68.4 | 58.3 | Tavily |
| hit@5 % | 84.0 | 74.8 | Tavily |
| fresh<30d % | 86.4 | 68.8 | Tavily |
| retrievability h | 7.8 | 15.4 | Tavily |
| cost/correct $ | $0.0059 | $0.0087 | Tavily |
| p50 latency ms | 688 | 926 | Tavily |
Head to Head — Web Extraction
| Metric | Tavily | Firecrawl | Winner |
|---|---|---|---|
| fidelity 0-1 | 0.79 | 0.91 | Firecrawl |
| JS gap Δ | 0.18 | 0.03 | Firecrawl |
| block rate % | 7.6 | 4.1 | Firecrawl |
| cost/correct $ | $0.0044 | $0.0031 | Firecrawl |
| schema validity % | — | 96.2 | Firecrawl |
Which Should an Agent Pick?
For accuracy-first agent workloads, the higher hit@5 vendor wins; for cost-sensitive high-volume use, prefer the lower cost-per-correct vendor. Both Tavily and Firecrawl should be evaluated on your own query mix — these are illustrative prototype figures.
Illustrative prototype. No verified vendor run has been published yet; every figure here is a placeholder and must not be cited as a measured result. Numbers are replaced when a snapshot’s first full run lands.