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 model transparency, 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. Managed LLM on paid plans (capped credits), self-host or cloud.

Feature Matrix

The model-transparency row is the structural difference. Tavily, Exa, and Perplexity all bundle an opaque LLM and mark up the tokens. fastCRW runs a managed LLM whose answer leg is metered in CRW credits with no separate token markup and a hard per-request cap — so the search/scrape credits and the synthesis credits live on one bill you can forecast. 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):

The structural advantage is that fastCRW's managed answer leg is metered in CRW credits with no separate token markup and a hard per-request cap, so a high-volume month stays bounded and forecastable in one currency. For occasional use where price doesn't matter, Tavily and Perplexity offer the lowest friction.

Important caveat: prices on bundled APIs can change without notice, and the underlying LLM choice is opaque. fastCRW's managed answer leg is priced in credits against your plan's published rate, with a capped worst case per request.

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://api.fastcrw.com/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"] },
  }),
});

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 — no separate LLM account to open, since the managed LLM runs the answer leg on paid plans. Total porting time: under an hour, and the answer cost lands in capped CRW credits instead of an opaque bundled markup.

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 capped, no-markup credit economics dominate.

One more reason teams pick fastCRW: regulatory or compliance constraints (banking, healthcare, government) often disallow sending data to an opaque third-party LLM. Self-hosting the AGPL-3.0 engine lets you run the entire search-answer pipeline — including the LLM step — on your own approved infrastructure, while fastCRW Cloud's managed LLM keeps the bill on one capped credit meter for everyone else.

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: how transparent and portable is your LLM dependency?

• fastCRW: managed LLM on a capped, no-markup credit meter — or self-host the AGPL-3.0 engine and run the whole pipeline yourself.
• Tavily / Exa / Perplexity: the API vendor owns it (model choice opaque, pricing locked, no self-host).

If you're building infrastructure that needs to last past a single funding round, a transparent, self-hostable pipeline is the safer bet.

Try It Yourself

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