Twitter Scraper Unlimited: tweets with no result cap

What sets the price of a run?

Three things, and only one of them is obvious. How many queries you send sets the query fee. What kind of query it is sets whether 40 tweets come free. And the query count also picks the per-item tier, which is where runs get expensive without warning.

• searchTerms

  $0.016per query

  ~40 tweets included

  The cheapest way in. One advanced-search string can stand in for many handles, and it counts as one query.

  from:NASA since:2026-01-01

• twitterHandles · startUrls

  $0.016per entry

  ~40 tweets included

  Handles, profile URLs and List URLs. Each entry is its own query at the same price.

  x.com/i/lists/78783491

• a single tweet or article URL

  $0.05per URL

  No tweets included

  One tweet costs three times a search and brings no free pages. Article URLs return the article body as content blocks.

  x.com/thedankoe/article/2023779299367809063

• The one nobody expects

  queries per run

  5× swing$0.0004 → $0.002

  Batching costs more here

  The per-item price is tiered on this number. Five queries bill items at $0.0004; six bill at $0.0008, for the same tweets.

  ≤5 · 6–10 · 11–30 · 31–100 · >100

This is the opposite of how the rest of the catalogue bills, where putting more work in one run saves money. Here a run is cheapest when it carries few queries that each return a lot, which is exactly what X’s query language is good at.

Listed on Apify as Twitter (X.com) Scraper Unlimited. Apidojo uses the short name.

Three ways to ask for tweets

The same actor answers three quite different questions: what is being said about something, what one account has published, and what a curated List is carrying. All three bill at $0.016 a query with roughly 40 tweets inside it.

{
  "searchTerms": ["from:NASA since:2026-01-01 filter:media"],
  "sort": "Latest",
  "maxItems": 1000
}

{
  "type": "tweet",
  "id": "1981345445986402472",
  "url": "https://x.com/NASA/status/1981345445986402472",
  "text": "Artemis II crew completed their final…",
  "createdAt": "2026-01-14T18:02:11.000Z",
  "retweetCount": 4821,
  "replyCount": 318,
  "likeCount": 39104,
  "author": { "userName": "NASA", "isVerified": true }
}

{
  "searchTerms": ["from:NASA since:2026-01-01 until:2026-06-30"],
  "sort": "Latest",
  "maxItems": 5000
}

{
  "type": "tweet",
  "text": "Watch the launch live from Kennedy…",
  "createdAt": "Mon Mar 02 09:14:55 +0000 2026",
  "isReply": false,
  "isRetweet": false,
  "isQuote": false,
  "author": {
    "userName": "NASA",
    "followers": 68204113,
    "isVerified": true,
    "isBlueVerified": true,
    "verifiedType": "business"
  }
}

{
  "startUrls": ["https://x.com/i/lists/78783491"],
  "sort": "Top",
  "maxItems": 2000
}

{
  "type": "tweet",
  "text": "Quarterly numbers are out and the story…",
  "createdAt": "2026-05-21T13:30:02.000Z",
  "quoteCount": 44,
  "bookmarkCount": 903,
  "author": { "userName": "example_analyst", "isVerified": false }
}

What a tweet record carries

Every query type returns the same object: the tweet, the six engagement counters X exposes, the author, and flags for what kind of tweet it is.

• 7

  The tweet

  Always present

  • id, url, twitterUrl
  • text
  • createdAt
  • lang
  • source, the posting client

• 5

  Engagement

  Five counters, no view count

  • likeCount, retweetCount
  • replyCount
  • quoteCount
  • bookmarkCount

• 8

  The author

  author, on every tweet

  • author.userName, id, name
  • author.url, twitterUrl
  • author.followers, following
  • author.isVerified, isBlueVerified
  • author.verifiedType
  • author.profilePicture

• 7

  Kind, context and articles

  Some conditional

  • isReply, isRetweet, isQuote
  • quoteId, what it quoted
  • card, place
  • article{ title, coverImage, contentState }

includeSearchTerms is worth turning on for any multi-term run: the listing says it adds a field carrying the term that found each tweet, though it does not name that field, so check one record before writing a parser against it. There is no view count in this actor’s output, the sibling Twitter Profile Scraper has one, this does not.

What to know before the first run

Six things shape a run here, and the first two are the ones that cost money if you learn them late.

• 01

  The item tier is set by query count, not volume

  Six queries put every item at $0.0008 where five put them at $0.0004. The same 2,000 tweets cost $0.80 or $1.50 depending on which side of that line the run falls.

• 02

  A single tweet URL costs $0.05 and includes nothing

  Three times a search query, with no free pages. For one tweet that is the price; for many, a conversation_id: search is far cheaper.

• 03

  The form shows eight inputs; nineteen more are documented

  The input schema declares searchTerms, twitterHandles, startUrls, sort, start, end, maxItems and includeSearchTerms. The listing documents seventeen more, including geo search (geotaggedNear, withinRadius, geocode, placeObjectId), engagement floors (minimumRetweets, minimumFavorites, minimumReplies), author filters (author, inReplyTo, mentioning), tweetLanguage and conversationIds. They are not in the form, so send them as JSON.

• 04

  start and end only apply to searchTerms

  The listing is explicit that they are ignored on startUrls and twitterHandles, and recommends putting the range inside the query with since: and until: instead. A date range set beside a list of handles does nothing.

• 05

  Latest can under-return, especially with until:

  The actor flags this itself. Switch sort to Top, drop until:, or use Latest + Top, which runs both searches at once.

• 06

  One run at a time

  The usage policy is a single concurrent run. Schedule sequentially rather than firing parallel runs.

• 07

  Tiered pricing applies to paid plans

  The actor states that this pricing is for paid Apify plans, and that free-plan pricing differs. Check the pricing tab on the listing if you are on the free plan.

• 08

  Public tweets only

  No login and no cookies, so protected accounts and deleted tweets return nothing.

Demo mode on a free Apify account allows 5 runs a month, 10 items in each.

Where the tier cliff bites

A run costs $0.016 a query plus the tier rate for every tweet past the roughly 40 each query includes. The rows below are ordered to show the cliff: rows four and five are the same 2,000 tweets, one query apart.

Computed from the two query events and the five item tiers the Apify Store API reports. Rows four and five are the argument for writing one good query instead of six plain ones: the same tweets, 88% more money.

Who needs tweets without a result cap?

Five kinds of work reach for this one over the flat-rate Tweet Scraper: social listening, crisis monitoring, academic research, finance and competitive intelligence. All of them want a whole conversation rather than a sample of it.

• Social listening teams

  Search X, one broad query

  Track a brand or campaign term across X and keep the whole result set, not the first page of it

  $0.40 per 1,000 tweets

• Crisis and reputation monitoring

  Search X, scheduled hourly

  Watch a term as it moves, where missing the tail of a spike is the whole risk

  $0.016 per check at 40 tweets

• Academic researchers

  A profile’s tweets, by date window

  Build complete account histories split into since:/until: windows, staying inside tier 1

  $2.00 per 5,000 tweets

• Finance and market research

  A List

  Read a curated List of analysts or tickers without maintaining the member list separately

  $0.80 per 2,000 tweets

• Competitive intelligence

  Search X with from: OR from:

  Follow several competitor accounts in one query, which keeps the run in the cheapest tier

  $0.40 per 1,000 tweets

Driving it from code

The actor is apidojo/twitter-scraper-lite. The one thing worth building into your code is the tier: because the per-item price depends on the number of queries, a batch loop that grows past five queries silently doubles its own item cost.

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

HANDLES = ["NASA", "ESA", "JAXA_en"]

# One query, not three: OR keeps the run in tier 1 at $0.0004 an item.
term = " OR ".join(f"from:{h}" for h in HANDLES) + " since:2026-01-01"

run = client.actor("apidojo/twitter-scraper-lite").call(run_input={
    "searchTerms": [term],
    "sort": "Latest",
    "includeSearchTerms": True,
    "maxItems": 5000,
})

for tweet in client.dataset(run.default_dataset_id).iterate_items():
    print(tweet["createdAt"], tweet["author"]["userName"], tweet["likeCount"])

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });

// Long histories split by date. Keep the window count at five or fewer
// and every item still bills at the tier 1 rate.
const windows = [
  'from:NASA since:2026-01-01 until:2026-04-01',
  'from:NASA since:2026-04-01 until:2026-07-01',
];

const run = await client.actor('apidojo/twitter-scraper-lite').call({
  searchTerms: windows,
  sort: 'Latest',
  includeSearchTerms: true,
  maxItems: 10000,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.length, 'tweets across', windows.length, 'queries');

curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~twitter-scraper-lite/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerms":["from:NASA filter:media"],"sort":"Top","maxItems":1000}'

Datasets export as JSON or CSV, or stream over the API. Every key used here is in the actor’s input schema, and the advanced-search syntax is X’s own.

Twitter Scraper Unlimited FAQ

Where Twitter Scraper Unlimited fits