WellMarked / blog / wellmarked-vs-firecrawl-vs-jina
Updated May 24, 2026 · 7 min read
If you're building anything that ingests the live web — a RAG pipeline, an autonomous agent, a research tool, a competitive intelligence feed — you've probably evaluated at least two of these three tools. They all solve the same surface-level problem: take a URL, return something an LLM can actually use. But they make very different bets about what "something useful" means, and the pricing models are different enough that choosing wrong can mean paying 5–7× more than you expected.
This page is not a hit piece on anyone. Firecrawl is genuinely great software. Jina Reader is genuinely clever. We built WellMarked because we had a specific itch that neither scratched — and we think it's worth being explicit about the tradeoffs.
Headline credit numbers are almost always misleading. Here's the worked arithmetic on a real workload — 1,000 extractions per month, the most common entry-level pipeline:
Basic scrape: 1 credit. AI extraction via /extract: 5 credits (and a separate subscription starting at $89/mo). Browser interaction: 2 credits per minute. FIRE-1 agent actions: billed dynamically and charged even on failure.
Note: the /extract AI endpoint is a separate subscription on top of the base plan. If that's your primary use case, budget accordingly.
Jina bills by output token count, not by request. A short news article and a long Wikipedia page cost completely different amounts. The same API key also drains your token balance for embeddings, reranking, and classification — so your reader budget competes with your embedding budget if you use Jina's full stack.
| Scenario | WellMarked | Firecrawl | Jina Reader |
|---|---|---|---|
| 1,000 basic scrapes | $29/mo fits well under Pro's quota | $5.33 Hobby: 1,000 of 3,000 credits | ~$0.05 token-metered, varies by page length |
| 1,000 AI extractions | $29/mo no 5× credit multiplier on Pro | $26.67 5 credits × $0.00533 on Hobby | varies separate /extract plan from $89/mo |
| 10,000 scrapes/month | $29/mo Pro plan — fills the quota exactly | $83.00 Standard plan required (100k credits) | varies token bundles; rate limits may throttle |
| 40,000 scrapes/month | $79/mo Growth plan — bulk + crawl included | $333.00 Growth plan (500k credits) for headroom | varies token bundles scale linearly; no flat tier |
| Bulk (50 URLs concurrently) | included Pro & Growth; atomic quota reservation | included Standard+ (batch scraping tier) | N/A single-page reader; no bulk endpoint |
| Feature | WellMarked | Firecrawl | Jina Reader |
|---|---|---|---|
| URL → clean Markdown | ✓ | ✓ | ✓ |
| Structured metadata | ✓ | ✓ | ✓ |
| JS rendering (Playwright) | ✓ | ✓ | ✓ |
| Bulk / concurrent extraction | ✓ | ✓ | ✕ |
| Full-site crawl | ✓ | ✓ | ✕ |
| Flat per-request pricing | ✓ | ✕ | ✕ |
| Free tier (monthly) | ✓ | ✕ | ✓ |
| Python SDK (PyPI) | ✓ | ✓ | ✕ |
| JavaScript / TypeScript SDK (npm) | ✓ | ✓ | ✕ |
| Typed responses + typed errors | ✓ | ✕ | ✕ |
| n8n community node | ✓ | ✓ | ✕ |
| llms.txt for AI agents | ✓ | ✕ | ✕ |
✓ = yes · ✕ = no. Verified May 2026.Spot an error? Let us know.
Firecrawl is the most featureful option of the three. It interacts with pages via a headless browser (clicking, filling forms, scrolling), does structured JSON extraction, and integrates natively with LangChain and LlamaIndex. If your job involves multi-step web workflows or structured JSON output, Firecrawl handles those today and WellMarked doesn't.
WellMarked covers the four pieces most RAG-pipeline builders actually need: single extraction, bulk concurrent extraction, full-site crawl (BFS from a root URL with depth + page caps), and an official n8n community node for no-code workflows. If the rest of Firecrawl's toolbox isn't on your roadmap, our flat per-request pricing usually wins on the bill.
The catch is the credit system. "1 credit = 1 page" is only true for the simplest case. AI-powered extraction costs 5 credits per call. Browser interactions are billed per minute. The advanced FIRE-1 agent is billed dynamically and charges you even on failure. The /extract endpoint — the one most developers building AI pipelines actually want — runs on a completely separate token-based subscription. Credits expire at month end and don't roll over. Budget for what you'll actually use, not the headline credit count.
Firecrawl is open source under AGPL-3.0 and self-hostable, which is a real differentiator if data residency or infrastructure control matters to you. WellMarked is a hosted SaaS — operationally simpler, no Docker / database / browser-pool plumbing on your side.
Jina Reader's API design is genuinely inspired: prepend https://r.jina.ai/ to any URL and you get back clean Markdown. No auth required for basic usage. No JSON body to construct. It's the fastest possible path from "I have a URL" to "I have readable text." For quick scripts, notebooks, and prototyping, nothing is faster to wire up.
The tradeoffs: billing is token-based and shared across Jina's entire API surface (embeddings, reranking, reader, classification all draw from the same bucket). There's no bulk endpoint — if you have 500 URLs, you're looping. Anonymous (keyless) requests are heavily rate-limited. The free tier's 1M tokens are marked non-commercial. And because cost scales with output token count rather than request count, a pipeline that mixes short news articles with long documentation pages will see wildly variable per-page costs.
Jina Reader is open source (Apache 2.0) and self-hostable via Docker. If you're already using Jina embeddings or reranking, the shared key and token pool can actually be a convenience.
WellMarked focuses on one thing: URL in, clean Markdown and structured metadata out. It doesn't automate browser interactions or compete with your embedding / reranking spend. The entire API surface is six endpoints, all authenticated with a Bearer token, all using flat per-request pricing with no multipliers.
The case for WellMarked comes down to predictability and pipeline fit. When you're building a production RAG system and projecting costs, you want to write requests × $0.0035 on a napkin and trust the number. Bulk extraction processes up to 50 URLs concurrently (Pro), 200 (Growth), or unlimited (Enterprise) in a single job, with per-URL failure isolation so one bad page doesn't abort the batch. Full-site crawl walks a site BFS from a root URL with per-plan depth and page caps (Pro: depth 5, up to 2,000 pages; Growth: depth 5, up to 10,000 pages; Enterprise: unlimited) and respects robots.txt.
Two official SDKs ship with the API — the Python package on PyPI (sync + async clients, typed exceptions, automatic wait_for_job polling) and the JavaScript / TypeScript package on npm (dual ESM + CJS, bundled .d.ts, runs on Node 18+, Deno, Bun, Cloudflare Workers, and the browser). Both expose the same polymorphic get_job / wait_for_job that handles bulk and crawl IDs interchangeably. For no-code workflows, an official n8n community node ships every endpoint as a typed n8n action.
What WellMarked doesn't do: browser automation beyond JS rendering, structured JSON extraction, or native LangChain / LlamaIndex integrations. If you need those, Firecrawl is the right answer.
429 rate_limit_exceeded error and a retry_after header telling you the seconds until reset. On Pro, Growth, and Enterprise, overages are billed at the plan rate ($0.0035, $0.0020, and $0.0012 respectively) at end of month via Stripe.POST /crawl walks a site BFS from a root URL — same-site links only (eTLD+1), robots.txt-respecting, with per-plan caps (Pro: depth 5, up to 2,000 pages; Growth: depth 5, up to 10,000 pages; Enterprise: unlimited). Only successfully-extracted pages count toward your quota — failed pages (timeouts, robots-disallowed, no-content) are not billed. The crawl returns a job ID you poll, or you can use wait_for_job in the SDKs to block until done.pip install wellmarked (sync + async clients, typed exceptions). The JavaScript / TypeScript SDK is npm install wellmarked (dual ESM + CJS, bundled types, runtime-portable). For no-code stacks, an n8n-nodes-wellmarked community node ships every endpoint as a typed n8n action./v1/scrape call or your Jina r.jina.ai/ prefix with a POST api.wellmarked.io/extract, add your wm_ Bearer token, and the response shape is equivalent. Or use an official SDK — pip install wellmarked in Python, npm install wellmarked in JavaScript / TypeScript — both handle auth, retries, and typed errors for you.1,000 requests/month, no credit card, no expiry. Up and running in under 5 minutes.