Firecrawl vs fastCRW in 2026 — Drop-in API Compatibility, Benchmarked

TL;DR

fastCRW is a Firecrawl-compatible web scraping, crawling, and search API that runs as a single static Rust binary instead of a multi-container stack. It implements the same /v1/scrape, /v1/crawl, /v1/map, and /v1/search surface as Firecrawl, so adoption is a base-URL swap. On Firecrawl's own public scrape-content-dataset-v1 (1,000 URLs, harness diagnose_3way.py, run 2026-05-08), fastCRW wins truth-recall (63.74% vs 56.04%) and p50 latency (1914ms vs 2305ms); Firecrawl wins raw scrape-success (89.7% vs 87.7%) and the p90 tail. Read the full distribution on /benchmarks.

What "drop-in compatible" actually means

It means you change one URL. fastCRW models its request shapes on Firecrawl's /v1/scrape, /v1/crawl, /v1/map, and /v1/search endpoints, so an existing Firecrawl SDK or HTTP client works against fastCRW once you point it at the fastCRW base URL. The honest caveat: a few metadata keys and error-envelope wording diverge, and Firecrawl-Cloud-only features are not matched. The full row-level diff is in the capability matrix.

The our Firecrawl Rust guide's self-hosted constructor (v1 FirecrawlApp::new_selfhosted, v2 Client::new_selfhosted — pin a version) also targets fastCRW directly, so Rust callers do not rewrite client code.

Benchmark: fastCRW vs Firecrawl head-to-head

Every number below comes from the same run: Firecrawl's public scrape-content-dataset-v1 (1,000 URLs, 819 with labeled ground truth), harness diagnose_3way.py, executed 2026-05-08, 0 thrown errors across 3,000 requests. Read the methodology before treating any figure as universal.

Feature / metric	Firecrawl	fastCRW
Truth-recall (of 819 labeled URLs)	56.04% (459)	63.74% (522)
Scrape-success (of 1,000 URLs)	89.7%	87.7% (877)
p50 latency	2305ms	1914ms
p90 latency	6937ms	14157ms — chrome-stealth fallback recovers hard URLs others drop
p99 latency	21107ms	15012ms
Thrown errors (of 3,000 requests)	0	0
API surface	/v1/scrape, /v1/crawl, /v1/map, /v1/search, /v1/extract, /v1/agent, /v1/deep-research	/v1/scrape, /v1/crawl, /v1/map, /v1/search, /mcp
Screenshot output	✅	❌ (formats: ["screenshot"] → HTTP 422)
Multi-URL batched extract	✅ standalone route	❌ (single-URL /v1/extract, managed-cloud-only)
/v1/agent (Spark models)	✅	❌
/v1/deep-research	✅	❌
Fire-engine anti-bot	✅	❌
Renderers	Playwright / Puppeteer	auto / http / lightpanda / chrome
MCP server	✅ official firecrawl-mcp-server	✅ built-in crw-mcp@0.6.0
Self-host footprint	~2-3 GB across 5 containers	one ~8 MB binary, 1 container (+optional sidecar)
Self-host dependencies	Postgres + Redis + workers	none — no Redis, Node.js, or containers required
License	proprietary (Cloud) / AGPL-3.0 (OSS)	AGPL-3.0
Standard managed plan	$83/mo, 100k credits	$69/mo, 100k credits
Self-host cost per 1k scrapes	hosted $0.83-5.33 per 1k	$0 (AGPL engine)

The p90 row needs its context. fastCRW's 14157ms p90 is higher than Firecrawl's 6937ms because fastCRW escalates URLs that fail a plain HTTP fetch to a chrome-stealth renderer — it spends latency to recover content that a faster failure would have dropped. That trade is visible in the recall column: 522 labeled URLs answered versus 459. If your workload is latency-bound on every request, Firecrawl's tighter tail matters; if it is recall-bound, fastCRW's escalation is the point.

Where Firecrawl wins

Firecrawl is the better choice when:

• You need screenshots. fastCRW returns HTTP 422 for formats: ["screenshot"] — there is no screenshot output in this release.
• You need multi-URL batched extract. Firecrawl Cloud has a standalone batched /v1/extract. fastCRW's /v1/extract is a managed-cloud-only, single-URL, 5-credit wrapper over /v1/scrape with formats: ["json"]; there is no /v1/batch/scrape.
• You need /v1/agent, /v1/deep-research, or Fire-engine anti-bot. None are matched. For cloudflare-protected JS-heavy SPAs, Firecrawl Cloud's anti-bot stack is stronger.
• Raw scrape-success is your top metric. Firecrawl returned content for 89.7% of the 1,000 URLs versus fastCRW's 87.7% — a real, if narrow, lead.
• A tighter latency tail matters more than recall. Firecrawl's p90 of 6937ms beats fastCRW's 14157ms.

Where fastCRW wins

fastCRW is the better choice when:

• Content accuracy matters most. 63.74% truth-recall (522 of 819 labeled URLs) versus Firecrawl's 56.04% (459) on Firecrawl's own dataset.
• Median latency matters. p50 1914ms versus 2305ms — the typical request is faster.
• Footprint matters. One ~8 MB Rust binary in a single container, with no Redis, Node.js, or containers required, versus Firecrawl self-host's ~2-3 GB across 5 containers. (Footprint figures are structural facts, not benchmark results.)
• Cost matters. $69/mo Standard versus $83/mo, and a $0-per-1k-scrapes self-host path under AGPL-3.0 versus Firecrawl hosted's $0.83-5.33 per 1k.
• You want MCP without an extra moving part. crw-mcp@0.6.0 is built into the same binary.

Migration flow

1. Read the capability matrix. If your code depends on screenshots, batched extract, /v1/agent, /v1/deep-research, or Fire-engine, stop here — stay on Firecrawl Cloud.
2. Test representative URLs in the fastCRW playground and diff the response against your current Firecrawl scrape call.
3. Point your Firecrawl SDK or HTTP client at the fastCRW base URL. Keep the four overlap-surface calls unchanged.
4. Adjust any code reading divergent metadata keys, and replace multi-URL batched /v1/extract with a loop or a /v1/crawl job.
5. Read the 1,000-URL benchmark and methodology and decide on your own workload.

Bottom line

Firecrawl vs fastCRW is not a "which is better" question — it is a trade. fastCRW gives you higher truth-recall, a faster median, a single-binary footprint, and a lower price, adopted with a base-URL swap. Firecrawl gives you screenshots, batched extract, /v1/agent, /v1/deep-research, Fire-engine anti-bot, a higher raw scrape-success rate, and a tighter latency tail. Pick by which column your workload actually depends on.

Related

• Firecrawl alternative — the full Firecrawl ↔ fastCRW capability matrix.
• Crawl4AI vs fastCRW — Python library vs deployable API.
• Jina vs fastCRW — hosted URL-to-markdown reader vs full scraper.
• Firecrawl vs Tavily — when search-API intent matters more than scraping depth.