# Context.dev vs. Parallel: a full scraping stack or focused retrieval?

## The short answer

Pick Context.dev when the hard part is getting pages: whole-site crawls, rendered HTML and screenshots, browser actions, schema-shaped JSON from a known page, or brand and people data on the same key. Pick Parallel when the hard part is getting the right passages to a model: objective-focused excerpts from up to 20 URLs in one synchronous call, search with page excerpts at $1 per 1,000 requests, and deep research that returns a source, reasoning, and confidence for every output field.

Parallel wrote this comparison. Every Context.dev figure below comes from Context.dev's own pricing page, product pages, or docs, read on November 14, 2026, and we've tried to be as specific about where it wins as where Parallel does.

## The products

Context.dev[Context.dev](https://www.context.dev/) puts a wide web-data toolkit behind one credit balance: Scrape (markdown, rendered HTML, screenshots, images, bytes, or CSS-parsed fields in one call), Map, Crawl (up to 500 pages a call, or larger sites through Batches), Search, Answers, Monitors, file parsing, brand and styleguide data, and people and company search. JavaScript rendering, anti-bot handling, and proxies are included in every scrape. It ships official SDKs for TypeScript, Python, Ruby, Go, and PHP, plus a hosted MCP server, and it's hosted only.

Parallel's APIs are built around retrieval for AI agents: Search, Extract, Task for deep research and enrichment, FindAll for entity lists, Entity Search, Monitor, Decisions, and an OpenAI-compatible Responses API. It runs its own web index and ships Python and TypeScript SDKs and a free hosted MCP server[MCP server](/mcp). It doesn't sell proxies, browser actions, screenshots, or a crawl endpoint, so if a site blocks automated access or you need every page of a domain, Context.dev covers ground Parallel doesn't.

## Extraction: reading pages you already have

Both turn a URL into LLM-ready markdown, including JavaScript-heavy pages and PDFs. The difference is what comes back and how you're billed for it.

A Context.dev Scrape request returns the formats you ask for from one URL for a base of 1 credit. Browser actions raise that to 2, query highlights add 1, and JSON extraction against your schema adds 4 when it succeeds, for 5 credits a page. Per Context.dev's pricing page[Context.dev's pricing page](https://www.context.dev/pricing), most failed requests aren't billed. Large URL lists go through Batches, which run in the background and deliver a webhook when they finish.

Parallel's Extract API[Extract API](/products/extract) takes up to 20 URLs in one synchronous request. Add an objective and keyword queries, and it returns ranked excerpts from each page aligned to that goal, the full page as markdown, or both, for $1 per 1,000 URLs. It handles JavaScript-heavy pages and PDFs, and a fetch policy chooses between Parallel's cached index and a live fetch. It doesn't return HTML, screenshots, or schema-shaped JSON, and it has no proxy or unblocking layer.

If you're indexing sites for RAG or pulling product fields from a known template, Context.dev's formats, crawl, and JSON extraction fit better. If an agent needs the few paragraphs that answer its question from a handful of URLs, Parallel's objective-focused excerpts send fewer tokens to the model, and the Task API[Task API](https://docs.parallel.ai/task/task-quickstart) handles typed fields when you need them.

## Search and research

Context.dev's Search API[Search API](https://www.context.dev/search-api) returns 10 to 100 live results per query with titles, URLs, descriptions, and relevance labels, and can attach query-relevant highlights or each page's full markdown in the same call. It costs 1 credit per 10 results, with highlights adding 1 credit per 10 results and markdown 1 credit per page. Freshness, domain, and country filters are included. Context.dev Answers takes a task and an example JSON object and returns structured findings with source URLs in one synchronous request: 10 credits in fast mode or 100 in ultra.

Parallel Search[Parallel Search](/products/search) runs on Parallel's own web index. It takes an objective plus keyword queries and returns ranked results with excerpts pulled from each page body, in four modes: Turbo (about 200ms, $1 per 1,000 requests), Fast (about 700ms, $1 per 1,000), Basic (about 1s, $5 per 1,000), and Advanced (about 3s, $5 per 1,000, the default). Ten results are included, and extra results cost $1 per 1,000.

For research, the Task API[Task API](https://docs.parallel.ai/task/task-quickstart) runs asynchronously across nine processors, from $5 to $2,400 per 1,000 runs, and returns output to your JSON schema with a citation, reasoning, and calibrated confidence for every field. Task Groups submit thousands of runs at once. The OpenAI-compatible Responses API returns cited answers synchronously for $10 to $250 per 1,000, and FindAll and Monitor cover entity lists and change tracking.

For a quick structured lookup in one call, Context.dev Answers is simpler. For research that needs minutes rather than seconds, or evidence you can audit field by field, Parallel goes further.

## Pricing

Context.dev sells monthly plans measured in credits, with metered overage on paid plans. Parallel charges per request, with no plan required. Context.dev's self-serve plans:

Here's what common jobs cost per 1,000, using Context.dev Pro ($0.90 per 1,000 credits) and Parallel's published prices[published prices](https://docs.parallel.ai/getting-started/pricing). On Context.dev Developer, credits cost about twice as much.

Check official documentation for current pricing.

## Throughput and limits

Context.dev caps concurrent requests per organization: 2 on Free, 10 on Developer, 100 on Pro, 250 on Growth, and 500 on Scale, with no per-minute cap by default on paid plans. A scrape waits up to 90 seconds by default, adjustable to 300.

Parallel meters requests per minute rather than concurrency: 600 for Search and Extract on the default plan, 1,500 on the Scale plan[Scale plan](/pricing), 2,000 Task runs a minute, and 300 Monitor creations a minute. Polling for results doesn't count against those limits, per Parallel's rate limit docs[rate limit docs](https://docs.parallel.ai/getting-started/rate-limits).

## Compliance

Context.dev says it's SOC 2 Type 2 compliant, publishes a trust center and status page, and offers a 99.9% uptime SLA, SSO, and an MSA and DPA on Enterprise.

Parallel Web Systems is SOC 2 Type II certified. The Scale plan ($1,000 a month) includes hybrid zero data retention, and Enterprise adds SSO, a custom MSA and DPA, a HIPAA BAA, and an uptime SLA. An EU endpoint serves Search in basic mode.

## Benchmarks

We couldn't find a public benchmark that runs Context.dev and Parallel on the same task as of November 14, 2026. Context.dev's benchmarks page[benchmarks page](https://www.context.dev/benchmarks) lists strong results on scraping boards, including first of ten providers on scrapingbench.com, and second of 13 on Openbenchmarks' factual lookup board, where Parallel isn't listed. On Openbenchmarks' web search boards[Openbenchmarks' web search boards](https://openbenchmarks.com/web-search), Parallel Basic leads multi-hop company search at 46.5 F1, and Context.dev isn't listed there. Parallel's own evals are on parallel.ai/benchmarks[parallel.ai/benchmarks](/benchmarks).

The fair reading: Context.dev has the stronger public record on fetching pages, Parallel on multi-step retrieval, and neither has been measured against the other. Run both on a sample of your own URLs and questions.

## When to use each

Choose Context.dev when ingestion is the job. Crawling whole sites, rendered HTML and screenshots, browser actions, schema JSON from known pages, anti-bot handling on every request, and brand or people data on the same key are all things it does and Parallel doesn't. Its per-page price on Pro is also slightly lower.

Choose Parallel when an agent reads the web at request time. Search returns page excerpts from Parallel's own index for $1 per 1,000 requests, Extract returns only the passages that matter from up to 20 URLs per call, and Task, FindAll, and Monitor cover research with per-field evidence, entity lists, and change tracking.

Plenty of teams use both: a crawler like Context.dev to keep a known corpus fresh, and Parallel for the open-web lookups an agent makes while it works.

## Frequently asked questions

### Is Context.dev cheaper than Parallel?

Per page scraped on a paid plan, yes: $0.90 per 1,000 on Pro against Parallel's $1. For search with page content, Parallel Turbo and Fast at $1 per 1,000 cost less than Context.dev's $1.80 for 10 results with highlights on Pro. Parallel needs no monthly plan, so its per-request prices apply from the first call.

### Does Parallel have a crawl endpoint?

No. Extract reads the URLs you pass, up to 20 per request, and can return up to 512 links found on each page. Use Context.dev's Crawl or Map when you need every page of a site.

### Can Parallel return JSON in my own schema?

Not from Extract, which returns markdown. The Task API returns output to your JSON schema, with a citation, reasoning, and confidence for each field, from $5 per 1,000 runs.

**Related reading: **The best web extraction APIs for LLMs[The best web extraction APIs for LLMs](/articles/best-web-extraction-apis) / Olostep vs. Parallel[Olostep vs. Parallel](/articles/olostep-vs-parallel) / Parallel vs. Firecrawl[Parallel vs. Firecrawl](/compare/firecrawl-vs-parallel) / Crawl4AI vs. Parallel[Crawl4AI vs. Parallel](/articles/crawl4ai-vs-parallel).