Reddit Dataset Builder for LLM Fine-Tuning and RAG
Upvoted question threads from r/askscience, r/AskHistorians, ELI5 and r/AskEngineers, cleaned up and downloadable as JSON or CSV. Change the subs to yours.
What this run is set to
The settings saved on this example. Every one of them is editable once you open it on Apify — these are a starting point, not a limit.
| Setting | Value | What it does |
|---|---|---|
Sources (subreddits or user profiles) | r/AskHistorians, r/explainlikeimfive, r/askscience +1 more | Any mix of subreddits and Reddit user profiles. |
Fetch method | rss | rss = no key/login needed (recommended, default). |
Sort | top | top, hot (trending), new (latest), rising, or controversial. |
Time range | year | Time window for 'top' and 'controversial' sorts (ignored for hot/new/rising). |
Max stories per subreddit | 50 | How many qualifying stories to return per subreddit. |
Minimum upvotes | 200 | Skip posts below this upvote count. |
Min words (short-form fit) | 30 | Skip stories shorter than this (too thin for a short). |
Text stories only | off | Keep only self/text-post stories (skip link/image posts) and apply the word-count fit. |
Clean narration text | on | Strip markdown/links/edit-stamps and produce TTS-ready sentences. |
Comments per post | 50 | Fetch up to this many top comments per post (0 = none). |
Pricing
$0.0005 per Reddit post = $0.5 per 1,000
| You are charged for | When | Price |
|---|---|---|
| Reddit post scraped | One Reddit post in the dataset. | $0.0005 |
Pay-per-event pricing: you are billed per result, not per subscription. Billing is handled by Apify on your own account. These are the live Apify store prices, in effect since 2026-08-04, and they are what you are actually charged.
What you get
A structured dataset — each result includes fields like:
authorcreatedUtcfetchedAtfitsShortflairhookScoreidisStorynarrationnumCommentsover18postTypereadTimeSecondsscoresubreddittitleselftextfetchedCommentCounturlExport every run as JSON, CSV or Excel, or send it to your app, a database, Google Sheets, or an AI agent.
More use cases for Reddit Scraper
- Try
- Reddit Relationship Stories for YouTube and TikTokReddit Horror Stories from r/nosleep for NarrationReddit Stock Sentiment: WSB, r/stocks and r/optionsReddit Crypto Sentiment Data from r/CryptoCurrencyReddit Trending Topics - Rising Posts in Niche SubsReddit Top Posts of All Time from Any Subreddit
Built on Reddit Scraper — every input, output field, price and the full how-to are on the tool page.
Where this tool sits
- Categories
- Social Media Scrapers
- Platforms