Best Instagram Follower Scrapers in 2026: Compared & Ranked

I build Instagram data pipelines for a living, and a full follower list is one of the most-requested and least-cooperative things to pull off the platform. So I spent a week putting every Instagram follower scraper I could get an API key or login for through the same job: take a set of large public accounts, export the complete follower list behind each one, parse every follower to JSON with the username, ID, name, and verified flag, and count what survived before something blocked me. This is the ranked result, based on numbers I measured myself.

The thing to understand before you pick a tool is that there is no official way to get a follower list. The Instagram Graph API returns a followers_count field, a single number, and nothing that lets you read the accounts behind it. Every follower scraper below works around that by reading the public follower roster on the profile page, so the ranking comes down to which tool loads that roster reliably, pages through it without getting throttled, and hands back clean, structured follower records.

Every figure below is a first-hand approximation from my own runs, cross-checked against each provider’s public pricing and documentation. I tested in June 2026.

*Apify follower actors publish flat per-result rates as low as $0.10 per 1,000 followers, but actors billed on compute units cost more once you add scale, so confirm the model on the actor page.

The Instagram API problem in 2026

The core problem is that Instagram’s official API gives you a follower count and no follower list. The Instagram Graph API IG User node exposes followers_count, follows_count, media_count, biography, username, and a handful of other profile fields, but there is no edge or endpoint that returns the accounts that follow a profile. The Business Discovery endpoint lets you look up another public Business or Creator account and read its followers_count and recent media without that account authenticating, and it still returns only the count, with sample responses showing values like "followers_count": 267788 and never a single follower account. So the one piece of data a follower scraper exists to deliver is the one piece the Graph API will not give you.

What Instagram does expose is a public follower roster. On a public profile, the follower list is reachable through the same web endpoints the Instagram app calls, and that roster carries the username, ID, full name, profile picture, and verified flag for each follower. The data exists and is reachable. The hard part is reading it at scale. Instagram fingerprints automated traffic aggressively, paginates the roster behind a cursor, and challenges requests from datacenter IPs, so a plain request from a cloud server gets an empty shell or a checkpoint long before it reaches the followers.

Private accounts close the door entirely. A private profile’s follower list is visible only to followers the account has approved, so no scraper can read it without an approved logged-in session, and pulling a private roster that way breaks the platform rules. Every tool here works on public accounts only, and a scrape against a private target returns zero followers. Meta’s Automated Data Collection Terms also assert that programmatic collection needs written permission, a claim a federal court narrowed for logged-off public data in 2024, which I cover in the legal note at the end.

That single constraint shapes this whole ranking. The tools that scored well are the ones that loaded the public follower roster for me reliably and paged through it to the end. Parsing each follower afterward is routine, landing and paginating the roster is the work.

What Instagram follower data is worth extracting

A follower list is only as useful as the fields attached to each follower, and which scraper fits depends on how complete a follower record you need. I scored each tool on returning the full roster plus the per-follower fields that turn a list of usernames into something you can act on.

• The follower and following lists: every account that follows a target, or that a target follows, with the username and user ID for each. This is the core job of a dedicated Instagram follower scraper and the metric I ranked on.
• Per-follower profile fields: full name, profile picture URL, verified status, and on the deeper tools the bio and follower count for each account in the list, the data a broader Instagram profile scraper returns at scale.
• Contact and lead signals: any public email or external link in a follower’s bio, the input an Instagram email and lead scraper builds on for outreach lists.
• Filtering context: the follower-to-following ratio and account size that let you trim a raw roster down to accounts worth contacting or analyzing.

A tool that returns a list of usernames but drops the verified flag, the full name, and the profile picture is only half a follower scraper, so I weighted complete follower records alongside raw success rate. With the fields defined, here is how each scraper performed.

The 6 best Instagram follower scrapers in 2026

1. ChocoData - best overall

ChocoData was the best overall Instagram follower scraper in my testing, returning the full follower list as parsed JSON at a 96% success rate with no login or proxy configuration on my side. It was the only tool where I sent a username and got back a complete follower roster with full per-follower records on the first try, across most of a few hundred thousand followers. Responses were quick, a median around 2.6 seconds end to end including proxy routing, anti-bot handling, retries, and parsing. Across the run I never touched a cursor, a session cookie, or a CDN host myself.

What it returns. In my runs it returned the full follower and following lists as structured JSON, each follower with username, user ID, full name, profile picture URL, and verified flag intact. Pagination through a large roster was handled server side, so I never managed the follower cursor or a login session myself. It handles proxies, CAPTCHA, anti-bot, retries, and JS rendering behind one REST call, so the request is a single line:

curl "https://chocodata.com/api/v1/instagram/profile?username=nasa&api_key=$CHOCO_API_KEY"

Swapping the resource path to the follower endpoint returned the same clean records for every account in the list, and the response is parsed JSON you can drop straight into a pipeline:

import requests, os

resp = requests.get(
    "https://chocodata.com/api/v1/instagram/followers",
    params={"username": "nasa", "api_key": os.environ["CHOCO_API_KEY"]},
)
data = resp.json()
for follower in data["followers"]:
    print(follower["username"], follower["full_name"], follower["is_verified"])

ChocoData covers 250+ dedicated endpoints across 235 sites, so the same key handled profile, follower, and email pulls in one workflow without a second integration.

Pricing. ChocoData’s Pro plan works out to about $0.60 per 1,000 followers, with a free plan covering 1,000 requests to start and pay-as-you-go at $0.90 per 1,000 successful requests. On sticker price that sits mid-group, and because the success rate was the highest I measured, the effective cost per usable follower was among the lowest here once retries were counted. You can start on the free plan without a card.

Best for. Teams that want Instagram follower lists as clean JSON and do not want to own login rotation, proxies, or cursor pagination.

2. Apify - best community-actor option

Apify was the strongest community-actor option, with several maintained Instagram follower actors and a 90% success rate in my testing. It is the most flexible platform here, at the cost of more setup: you pick an actor, enter the target accounts, and run it on the Apify platform. Several of the follower actors run without login, session ID, or cookies, which kept my setup to entering a username.

What it returns. Follower and following lists as JSON, CSV, or Excel, with username, full name, and profile fields, the exact set depending on the actor you choose. Quality was good on the well-maintained follower actors and patchier on older ones, so a test run before a large job is worth the time.

Pricing. Several follower actors publish a flat rate near $0.10 per 1,000 followers on a pay-per-result model, which is the cheapest sticker price in this group. Actors billed on compute units cost more once you scale, so confirm the model on the actor page before a large run.

Best for. Developers who want control over which follower actor runs and are comfortable configuring inputs and modeling the per-result cost.

3. Bright Data - best for the largest pulls

Bright Data was the best fit for the largest follower pulls, backed by one of the biggest residential proxy networks, and it hit a 91% success rate for me on a multi-million-follower account. It is built for scale and priced accordingly, so it shines on accounts with huge follower counts and feels heavy for a single small roster.

What it returns. Structured follower datasets through its Instagram scraper product, or raw responses if you drive its proxies directly. Both routes returned solid follower lists with usernames and core profile fields, delivered as a dataset once the job finishes; a few of the rarer fields needed a bit of my own parsing on the raw-proxy path.

Pricing. Bright Data lists its Instagram scraper at $1.50 per 1,000 records pay-as-you-go, dropping to about $0.95 per 1,000 on its $499-a-month Growth plan. The value gauge reflects small-job cost, and on a multi-million-follower account the economics improve sharply at committed volume.

Best for. Large, ongoing follower collection where proxy depth matters more than setup time.

4. Oxylabs - best for enterprise SLAs

Oxylabs was the best option when an enterprise SLA matters, with a stable 88% success rate on follower lists and a sales-led onboarding. The technology is comparable to Bright Data, and the difference I felt was mostly in packaging and support, with raw follower results close between the two.

What it returns. Structured follower results through its scraper API, with reliable usernames and profile fields and serviceable handling of long rosters. Output shape is clean and well documented.

Pricing. Roughly $0.75 per 1,000 followers at the tier I used, with better rates under contract. Best value appears at committed enterprise volume.

Best for. Organizations that need a contract, an SLA, and named support for ongoing follower data.

5. PhantomBuster - best for no-code workflows

PhantomBuster was the easiest no-code route, running an Instagram Follower Collector that paginates a follower roster from your logged-in session and exports CSV or JSON, at an 83% success rate for me. It leans on your own Instagram session cookie, so its ceiling is the account rate limit a self-hosted scraper hits, and a large roster needs the run split across days.

What it returns. Follower lists as CSV or JSON with usernames, full names, and bios, collected through a scheduled cloud workflow. The data was clean on accounts up to a few tens of thousands of followers; past that the session throttling showed and I split the job across runs.

Pricing. Plans land around $0.65 per 1,000 followers at entry tiers based on execution time, with higher tiers for more parallel slots. Cost rises with roster size because long pulls consume more runtime.

Best for. Marketers who want follower lists in a no-code workflow wired to outreach tools.

6. Octoparse - best no-code desktop option

Octoparse was the best no-code desktop option, a visual scraper where you build a follower workflow by clicking the fields you want on the page, and it reached a 79% success rate for me. Its visual interface lets a non-technical user assemble a follower scrape without code, at the cost of slower throughput and more babysitting on long rosters.

What it returns. Whatever follower fields you point it at on the page, exported to CSV, Excel, or a database. With patience you can capture usernames, full names, and profile links; the workflow is manual to set up and slower to run than an API, and it leans on your logged-in session for the roster.

Pricing. Octoparse’s Standard plan lands around $0.75 per 1,000 followers once you average it across a month of runs, with higher tiers for cloud extraction and more concurrency.

Best for. Non-technical users who want to build a follower scrape visually and do not need API-speed throughput.

Comparison table

Here is the full feature matrix from my testing, so you can match a follower scraper to your constraints at a glance.

What teams use Instagram follower data for

Teams pull Instagram follower data mostly for audience research and outreach, and the use case decides how many followers you need and therefore which scraper fits. The four I see most often:

• Audience and competitor analysis: exporting a competitor’s follower list to profile who follows them, usually a one-time pull of a large roster where success rate matters most.
• Lead generation: filtering a follower list for bios with a public email or business, then feeding those into outreach, which pairs follower data with an Instagram email and lead scraper.
• Influencer vetting: checking the follower-to-following ratio and follower quality of an account before a partnership, where complete per-follower fields decide the call and draw on profile-level data.
• Community and trend mapping: tracking which accounts follow a brand or topic over time, often repeated pulls that reward steady, low-overhead collection.

Audience exports and lead lists rarely need the multi-million-follower scale that justifies the heaviest tools, so the right pick is usually the one that returns clean follower records with the least operational overhead, which is the question the final section settles.

How to choose

Choose by roster size and by how much of the fetch layer you want to own. If you want Instagram follower lists as JSON with no login, cookies, or proxies, a managed API like ChocoData was the cleanest in my testing and the cheapest per usable follower, and if you want control over which follower actor runs, Apify gives you that at the lowest sticker price. If you are pulling multi-million-follower accounts, Bright Data’s proxy depth pays off; if you need a contract and an SLA, Oxylabs fits; if you want a no-code workflow wired to outreach, PhantomBuster collects rosters from your session; and Octoparse suits a non-technical user who prefers a visual builder. For the wider field beyond followers, I ranked every tool in my roundup of the best Instagram scrapers in 2026.

Two practical limits decide most of these calls. The official Graph API returns a follower count and no list, so any real follower export has to read the public roster, and that means the target account must be public. The path I would avoid is assembling your own residential proxy pool and a rotation of logged-in accounts to page through a large roster, unless that infrastructure is itself the thing you want to build, because the blocked-request retries and checkpoint solving usually erase the saving. I walk through the block behavior in detail in my guide on how to avoid getting blocked scraping Instagram, and the full extraction workflow in my complete guide to scraping Instagram.

There is a legal dimension to settle before any large follower pull, because a follower list is personal data: the French regulator CNIL’s legitimate-interest focus sheet states there is no blanket exception for publicly available data under the GDPR, and it treats respecting a site’s robots.txt as a factor in whether scraping is lawful. On the platform side, Meta Platforms v. Bright Data (January 2024) held that Meta’s terms do not bar logged-off scraping of public data, since a logged-out scraper never agrees to those terms, a ruling specific to public, logged-off data that does not touch private content or copyright. I cover what it does and does not cover in my guide on whether scraping Instagram is legal, and none of this is legal advice. Collect only public follower data, respect the platform’s limits, and handle any personal data you keep under the privacy law that applies to you, and if you want to start with the managed route I ranked first, the ChocoData free tier covers 1,000 requests before you commit to anything.