CRW vs Tavily vs Exa vs Perplexity API (2026): Search-Answer Compared

The "search → AI answer" category went from one product (Perplexity) in 2024 to four serious API players by mid-2026: Tavily, Exa, Perplexity, and fastCRW. They all do roughly the same thing — turn a query into a sourced answer — and differ on the dimensions that actually matter once you're past the demo.

This piece compares them on BYOK support, citation handling, pricing model, self-hosting, and migration cost. fastCRW v0.7.0 shipped its answer: true flag on 2026-05-12, which is the trigger for this comparison.

The Category in One Sentence Each

• Perplexity API — search-answer as a closed product. One vendor, bundled LLM, no self-host.
• Tavily — search-answer optimized for RAG agents. Strong defaults, locked pricing, hosted only.
• Exa — semantic search-first with optional answer. Good for "find me pages similar to X."
• fastCRW — search + scrape + answer as one open-source API. BYOK LLM, self-host or cloud.

Feature Matrix

The BYOK row is the structural difference. Tavily, Exa, and Perplexity all bundle the LLM. fastCRW separates the search/scrape infrastructure (where they charge credits) from the LLM call (where you bring your own key). That single decision changes the pricing math.

Pricing

Pricing is the dimension most often hand-waved in API comparisons. Here's the real math at mid-2026 prices for a typical search-answer query (1 search, 3 scraped sources, ~5,000 input tokens, ~100 output tokens):

For high-volume use (10k+ queries/month), fastCRW + DeepSeek wins by 2–3× on price and lets you choose the model. For occasional use where price doesn't matter, Tavily and Perplexity offer the lowest friction (one API key, no LLM account).

Important caveat: prices on bundled APIs can change without notice, and the underlying LLM choice is opaque. With BYOK, you see the model name and the per-token rate.

Citation Quality — Same Query, Four APIs

We ran the same query through all four APIs: "what is the Rust borrow checker". Here's a side-by-side summary of what came back (paraphrased for length, not literal output):

Citation quality is roughly equivalent across all four for well-known queries. Differences appear on the long tail: Tavily and Perplexity occasionally over-cite (5+ sources for a one-sentence answer). fastCRW caps at 20 and validates server-side, but on this benchmark the LLM emitted 3 citations naturally.

For niche or fresh queries (e.g., "what shipped in CRW v0.7.0 yesterday"), fresh public-web search-answer APIs (Tavily, Perplexity, fastCRW with scrape) outperform Exa, which leans toward semantic similarity over a possibly-stale index.

Latency

Wall-clock latency on a small synthetic run (10 queries each, median):

Perplexity and Exa are faster because they index pages ahead of time and skip the live-scrape step. fastCRW and Tavily are slower because they scrape on the fly. Tradeoff: indexed providers can miss content that changed today; live-scrape providers see today's web.

If you need sub-5-second answers, set answerTopN: 2 on fastCRW and pre-cache popular queries. If freshness matters more than latency, stay with live scrape.

When to Pick Each

Migration: Tavily → fastCRW (Code Diff)

Tavily's /search with include_answer: true maps directly to fastCRW's /v1/search with answer: true. The fields rename slightly:

// Tavily (before)
const r = await fetch("https://api.tavily.com/search", {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    api_key: process.env.TAVILY_API_KEY,
    query: "what is rust borrow checker",
    search_depth: "advanced",
    include_answer: true,
    max_results: 5,
  }),
});

// fastCRW (after)
const r = await fetch("https://fastcrw.com/api/v1/search", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    Authorization: `Bearer ${process.env.CRW_API_KEY}`,
  },
  body: JSON.stringify({
    query: "what is rust borrow checker",
    limit: 5,
    answer: true,
    answerTopN: 3,
    scrapeOptions: { formats: ["markdown"] },
    llmProvider: "openai-compatible",
    llmModel: "deepseek-chat",
    baseUrl: "https://api.deepseek.com/v1",
    llmApiKey: process.env.DEEPSEEK_API_KEY,
  }),
});

Response field rename: Tavily's answer + results becomes fastCRW's data.answer + data.results + data.citations. Tavily's flat answer doesn't carry structured citations; fastCRW does.

If you were already running Tavily for RAG, the migration is one fetch call swap, plus opening a DeepSeek/OpenAI/Anthropic account for the LLM. Total porting time: under an hour. Steady-state cost drops 2–3× depending on your LLM choice.

What About Perplexity's Brand?

Perplexity has the strongest consumer brand of any search-answer product. For B2C apps where users recognize "powered by Perplexity," that brand has value beyond the technical merits. For B2B apps, infrastructure, agent workflows, and internal tools, brand value approaches zero and the BYOK economics dominate.

One more reason teams pick fastCRW: regulatory or compliance constraints (banking, healthcare, government) often disallow sending data to a third-party LLM bundled inside an external API. BYOK lets you route LLM calls through your existing approved provider (Azure OpenAI with PHI agreements, on-prem Llama, etc.) while keeping the rest of the search-answer pipeline external.

The Real Question Behind All of This

"Search-answer" is a feature that used to be a product. By 2027, it'll be a checkbox on every search API. The decision in 2026 is: who do you want to own your LLM dependency?

• fastCRW: you own it (BYOK, pick any provider).
• Tavily / Exa / Perplexity: the API vendor owns it (model choice opaque, pricing locked).

If you're building infrastructure that needs to last past a single funding round, owning the LLM dependency is the safer bet.

Try It Yourself

• Build a working answer engine in 50 lines
• Pair DeepSeek with /scrape for cheap summaries
• v0.7.0 release notes
• Search-answer docs
• Detailed Tavily comparison