Transparent feature-by-feature comparison with Tavily and Perplexity API.
We let the numbers speak.
| SearchAPI search.ourweb.ink | Tavily tavily.com | Perplexity perplexity.ai/api | |
|---|---|---|---|
| Accuracy | |||
| SimpleQA Benchmark | 94.3% | ~70-80%* | ~85%* |
| Answer extraction | ✓ Multi-phase LLM | ✓ LLM extraction | ✓ Built-in LLM |
| Source citations | ✓ Full excerpts | ✓ URLs | ✓ Inline citations |
| Search Sources | |||
| Google search | ✓ | ✓ | ✓ |
| Bing search | ✓ | ✕ | ✓ |
| Wikipedia deep parse | ✓ Tables + Wikidata | ✕ | ✕ |
| Academic papers (CrossRef) | ✓ | ✕ | Partial |
| Game/media wikis (Fandom) | ✓ 13+ wikis | ✕ | ✕ |
| Full page fetching | ✓ | ✓ | ✕ |
| Research Pipeline | |||
| Multi-phase research loop | ✓ 5 phases | ✕ Single pass | ✕ Single pass |
| Auto-rephrase on failure | ✓ | ✕ | ✕ |
| Specialized source fallback | ✓ | ✕ | ✕ |
| Phase transparency | ✓ Full trace | ✕ | ✕ |
| Pricing | |||
| Free tier | ✓ 100/day | ✓ 1,000/mo | ✕ |
| LLM extraction cost | $0 (free model) | Included | $5/1K queries |
| Pro plan | $29/mo | $100/mo | $20/mo + per-query |
| Developer Experience | |||
| Embeddable widget | ✓ | ✕ | ✕ |
| Interactive playground | ✓ | ✓ | ✕ |
| Research mode UI | ✓ | ✕ | ✕ |
*Estimated. Tavily and Perplexity do not publish official SimpleQA scores. SearchAPI's 94.3% is verified on 300 sequential SimpleQA questions.
Most search APIs do a single pass: search Google, return snippets. If the answer isn't in the first page of results, you get nothing.
SearchAPI runs a 5-phase research loop. If snippets fail, it fetches full pages. If those fail, it searches Wikipedia directly. Then it rephrases the question and tries again. Finally, it checks specialized databases for academic papers and game data.
This multi-phase approach is why SearchAPI achieves 94.3% on SimpleQA — significantly higher than single-pass alternatives.
Choose SearchAPI when accuracy matters most — factual question answering, research assistants, knowledge-intensive applications, or when you need specialized sources (academic, gaming).
Choose Tavily when you need a simple, well-documented search API with good LangChain/LlamaIndex integration and don't need the highest accuracy.
Choose Perplexity when you want a full conversational search experience with its own LLM, and don't need a standalone API.