rasterly vs ScrapeGraphAI — render + read + extract in one API

Q: Where is ScrapeGraphAI stronger than rasterly?

LLM-native extraction depth and open source. ScrapeGraphAI builds graph pipelines around an LLM (SmartScraperGraph for single pages, SearchGraph to search then scrape top results, multi-source graphs) and is MIT-licensed with a large community, so you can self-host and run it against your own model. If deep prompt-driven extraction or self-hosting is the requirement, ScrapeGraphAI is the specialist.

Q: Can I use both together?

Yes, and it is a reasonable setup. Use ScrapeGraphAI where you need deep LLM extraction, and rasterly for the rendering layer it does not cover — screenshots, PDF and cheap clean-Markdown reads — under one key with a flat price.

ScrapeGraphAI is the LLM-native extraction specialist; rasterly is the leaner all-in-one render layer. ScrapeGraphAI builds graph pipelines around a language model — describe the data in a prompt and get JSON, or search then scrape the top results — and it is MIT-licensed with a large community you can self-host. If deep, prompt-driven extraction is your bottleneck, it is purpose-built for that and we will not pretend to out-extract it. rasterly does the core web jobs — URL → clean Markdown (read), site → Markdown for RAG (crawl), URL → structured JSON (extract) — and adds screenshots and PDF as first-class outputs, which ScrapeGraphAI does not produce, from $0.90 per 1,000 renders. Pick by your bottleneck: deep LLM extraction and self-hosting point to ScrapeGraphAI; one cheap hosted API for rendering plus reading plus extracting points to rasterly.

If you are building on ScrapeGraphAI

Three things tend to matter once web-context is in a paid product:

The visual side is missing. ScrapeGraphAI extracts data; it does not render. If you also need a screenshot of the page or a PDF of it — for previews, proofs, thumbnails, archival — that is a second vendor. rasterly folds format=png, format=jpeg and format=pdf into the same API and key, with delay, wait_for, element capture and direct S3 upload.
Flat price vs LLM-metered cost. ScrapeGraphAI runs a model on every extraction, so cost tracks LLM usage and page complexity. rasterly's read and screenshot are a flat per-render price with no per-call model cost; extract for JSON-LD, OpenGraph and tables is deterministic and included. If your hot path is reads and renders rather than deep LLM extraction, the bill is more predictable.
One key for the whole web layer. read + crawl + extract + screenshot + PDF + change-monitoring on a single key, plus a pay-per-call endpoint over x402 on Base for agents with no signup.

The real difference

	rasterly	ScrapeGraphAI
Prompt-driven LLM extraction (natural language → JSON)	Basic — schema or prompt with your key	Yes — its core, deeper
Search across many sites, then scrape (SearchGraph)	No — crawl is same-origin	Yes
URL → clean Markdown (JS-rendered)	Yes — read	Extraction-focused, not a Markdown-out primitive
Deterministic extract (JSON-LD / OG / tables), no LLM cost	Yes — included	LLM on every extraction
Screenshots (png / jpeg)	Yes — first-class	No
HTML / URL → PDF	Yes — format=pdf	No
Animated-page capture (delay, wait_for, S3 upload)	Yes	No
Open-source, self-hostable	No — hosted API	Yes — MIT, ~30k stars
MCP server for agents	Yes — npx rasterly-mcp	Yes
SSRF protection out of the box	Enforced	Your responsibility when self-hosting
Pricing model	Flat, from $0.90 / 1,000	Credit / LLM-usage based

Honest line: on prompt-driven LLM extraction and on being open-source and self-hostable, ScrapeGraphAI is the stronger, more specialized tool, and rasterly does not match its extraction depth today. rasterly wins on the rendering it does that ScrapeGraphAI does not — screenshots and PDF — and on one flat-priced API for read, crawl and extract alongside them.

On price

The two meter differently, so a tier-for-tier table would be misleading. ScrapeGraphAI runs a language model per extraction and prices in credits, so your cost scales with LLM usage and page complexity, and with whichever model you point it at when self-hosting. rasterly prices per render at a flat rate, with reads and screenshots carrying no per-call model cost and deterministic extract included.

Tier	rasterly	ScrapeGraphAI
Free	100 renders / mo, no card	Free OSS lib; hosted free credits
Entry paid	$9 (Starter, 10k renders)	Credit-based, see their pricing
Effective per 1,000	$0.58–$0.90	Varies with model + page

Rule of thumb: if you mostly read pages and render screenshots or PDFs, rasterly's flat render price is cheaper and easier to forecast. If you mostly run deep LLM extraction over messy pages, price it on ScrapeGraphAI's terms — the LLM work is the cost, and that is exactly what it is built to do well.

Using both

They are not mutually exclusive. A common split: ScrapeGraphAI for the deep, prompt-driven extraction it specializes in, and rasterly for the rendering layer it does not cover.

rasterly — read a page to clean Markdown

curl "https://api.rasterly.dev/v1/read?url=https://stripe.com" \
  -H "X-Api-Key: sk_live_..."

rasterly — screenshot the same page (ScrapeGraphAI cannot)

curl "https://api.rasterly.dev/v1/screenshot?url=https://stripe.com&format=png" \
  -H "X-Api-Key: sk_live_..." -o shot.png

Structured data is /v1/extract?url= (JSON-LD, OpenGraph, tables, or a schema); a PDF is format=pdf; a site crawl is /v1/crawl?url= — all under one X-Api-Key. For search-then-scrape across many sites, or deep natural-language extraction, that stays ScrapeGraphAI's job.

FAQ

Is rasterly a replacement for ScrapeGraphAI?

It depends on the job. If your core need is prompt-driven LLM extraction, or search-and-scrape across many sites, ScrapeGraphAI is purpose-built for that with a large open-source community. rasterly's extract is lighter. Where rasterly is the better fit is the rendering side, screenshots and PDF, which ScrapeGraphAI does not do, plus clean Markdown, crawl and extract in one flat-priced API.

What does rasterly do that ScrapeGraphAI does not?

Visual rendering. rasterly turns any URL into a PNG, JPEG or PDF as first-class outputs, with delay, wait_for, element capture and direct S3 upload. ScrapeGraphAI is an extraction engine and does not produce screenshots or PDFs.

Where is ScrapeGraphAI stronger than rasterly?

LLM-native extraction depth and open source. It builds graph pipelines around an LLM (SmartScraperGraph for single pages, SearchGraph to search then scrape, multi-source graphs) and is MIT-licensed with a large community, so you can self-host against your own model. For deep prompt-driven extraction or self-hosting, ScrapeGraphAI is the specialist.

Can I use both together?

Yes. Use ScrapeGraphAI where you need deep LLM extraction, and rasterly for the rendering layer it does not cover — screenshots, PDF and cheap clean-Markdown reads — under one key with a flat price.

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ScrapeGraphAI features observed August 2026 from its public open-source repository and site, shown for comparison only; check scrapegraphai.com for current details. ScrapeGraphAI is an LLM extraction library and hosted API that meters differently from rasterly, so the tables above are for rough orientation, not an exact per-page equivalence. rasterly is an independent product, not affiliated with, endorsed by, or sponsored by ScrapeGraphAI.