What is the cheapest API that works on LinkedIn?

Sort the ranked table by cost per successful request and read down to the first provider still clearing LinkedIn this run. Lower priced APIs further down often fail too many requests for their sticker price to be meaningful.

Best Web Scraping APIs for LinkedIn: July 2026 Benchmark

Name: linkedin.com Web Scraping API Benchmark
Creator: Scrapeway

Benchmarks run by the Scrapeway team · Last updated: August 14, 2026 · How we benchmark

Scrapfly is the best web scraping API for LinkedIn, with a 97% success rate across 8 web scraping APIs benchmarked against live LinkedIn pages in July 2026. 3 of the 8 cleared LinkedIn reliably enough to recommend.

LinkedIn is protected by Arkose Labs and gates most data behind a login wall, so most scraping APIs either fail it or pay for it in speed and cost. The benchmark is refreshed twice a month, with no affiliate links and no sponsors.

Ranked by live LinkedIn success rate, best first:

🥇 Scrapfly: 97% success on LinkedIn
🥈 Scrapingdog: 92% success on LinkedIn
🥉 WebScrapingAPI: 90% success on LinkedIn

All 4 web scraping APIs for LinkedIn, ranked

#	Service	Success	Speed	Cost/1k		Code
1 🥇	Scrapfly	97%	32.7s	$6.83	(237) ★ 4.9	code
2 🥈	Scrapingdog	92%	0.2s	$10.0	n/a	code
3 🥉	WebScrapingAPI	90%	14.8s	$2.71	n/a	code
4	Scraperapi	88%	16.6s	$14.7	(62) ★ 4.6	code

Data range Jul 31 to Aug 14

Ranking history: web scraping APIs for LinkedIn over time

LinkedIn target ranking history

The 4 web scraping APIs for LinkedIn, reviewed

1. Scrapfly: 97% success on LinkedIn

On LinkedIn	Speed	Cost/1k	Overall	From
97%	32.7s	$6.83	#1 of 4	$30/mo

LinkedIn puts Arkose Labs in front of sessions it flags and shows an authwall to unauthenticated requests, with public profile and job data served through its internal API rather than the visible HTML. Scrapfly cleared 97% here by generating a genuine browser fingerprint and passing the challenge, so it reaches the public profile and job data instead of an authwall. Because it only bills for successful requests, the authwall and challenge pages LinkedIn returns don't quietly run up the cost.

At $6.83 per 1,000 successful requests and 32.7s average response time, the figures are strong for a challenge gated site like LinkedIn. The 97% success rate is the headline, and the ranking history above shows how that rate has held across previous runs.

Pros:

Highest success rate in the LinkedIn benchmark this run, clearing the authwall and Arkose Labs' challenge on public pages
Only charges for successful scrapes, so authwall and challenge pages cost nothing
One asp flag plus residential proxies handles LinkedIn with little tuning
First class SDKs for Python, TypeScript, Go, and Rust, plus a Scrapy extension

Cons:

Credit cost per request rises once ASP, JavaScript rendering, or residential proxies are enabled
The entry (Discovery) plan caps concurrency at 5, so large profile crawls need a higher tier
The free tier is a single batch of 1,000 credits, enough to prototype but not to benchmark at volume

2. Scrapingdog: 92% success on LinkedIn

On LinkedIn	Speed	Cost/1k	Overall	From
92%	0.2s	$10.00	#2 of 4	$40/mo

Scrapingdog offers low entry pricing and a simple API, without first party SDKs, and it markets a dedicated LinkedIn endpoint. LinkedIn shows an authwall to unauthenticated requests, and Arkose Labs serves an interactive challenge to sessions it flags. On LinkedIn it cleared 92% this run.

Pros:

Low entry pricing
Simple API with a dedicated LinkedIn endpoint

Cons:

No first party SDKs
Reviewers frequently cite slow, email only support with no live chat option

3. WebScrapingAPI: 90% success on LinkedIn

On LinkedIn	Speed	Cost/1k	Overall	From
90%	14.8s	$2.71	#3 of 4	$19/mo

WebScrapingAPI covers a broad range of language SDKs behind a simple REST interface, so it drops into most stacks without a client library, and it supports async and batch submission for queued jobs. The scorecard carries this run's speed and cost. On LinkedIn it cleared 90% this run.

Pros:

Broad language SDK range behind a simple REST interface
Async and batch submission for queued jobs

Cons:

LinkedIn's authwall pages make it easy to keep paying unless you check content
Support tickets often go unanswered for days, per user reviews

4. Scraperapi: 88% success on LinkedIn

On LinkedIn	Speed	Cost/1k	Overall	From
88%	16.6s	$14.70	#4 of 4	$49/mo

Scraperapi is built around a fast request path. When it clears a request it tends to return quickly, which suits latency sensitive lookups that can absorb retries. LinkedIn's authwall and Arkose Labs' challenge sit in front of the public profile and job data, and the scorecard carries how it did on that this run. On LinkedIn it cleared 88% this run.

Pros:

Fast when it clears, with a simple integration
Broad language SDK support

Cons:

Login required flows are off limits, and much of LinkedIn sits behind a login
Geotargeting is gated by plan (US and EU only until the Business tier)

COMPARISON

About scraping LinkedIn

LinkedIn is the largest professional network, and the data people scrape from it is mostly career detail. That means public profile headlines and summaries, current and past positions, skills, education, company pages, and public job postings with titles, companies, locations, and descriptions. The subset that is publicly reachable without an account is limited to public profile and job pages.

LinkedIn is a JavaScript heavy app that serves data through its internal (Voyager) API rather than the page HTML, and it shows an authwall to unauthenticated or suspicious requests. Much of the platform, including full profiles, connections, and feeds, sits behind a login and is out of scope for public scraping. The benchmark targets public profile and job data only.

AUTOMATION

LinkedIn is protected by Arkose Labs, which serves an interactive challenge to sessions it flags. Arkose Labs is not one of the benchmarked antibot pages in this series, so there is no dedicated page to link. The key point for scraping LinkedIn is that its authwall and challenge pages return without a hard error status, so success has to be measured on response content, not status codes.

linkedin_scraper.py

import json
from parsel import Selector

# install using `pip install scrapfly-sdk`
from scrapfly import ScrapflyClient, ScrapeConfig, ScrapeApiResponse

# create an API client instance
client = ScrapflyClient(key="YOUR API KEY")

# create scrape function that returns HTML parser for a given URL
def scrape(url: str, country: str="", render_js=False, headers: dict=None) -> Selector:
    api_result = client.scrape(ScrapeConfig(
            url=url,
            headers=headers,
            asp=True,
            render_js=render_js or False,
            cache=False,
            cache_ttl=900,
            method='GET',
    ))
    return api_result.selector

url = "https://www.linkedin.com/in/adammgrant"
selector = scrape(url)

# big chunk of the dataset can be found in microdata markup:
data = json.loads(selector.xpath("//script[@type='application/ld+json']/text()").get())

# the resulting dataset is pretty big but here are some example fields:
person_data = next(d for d in data['@graph'] if d['@type'] == "Person")
from pprint import pprint
pprint(person_data)