Minexa.ai vs LLM scrapers: what extraction really costs per page

The honest break-even point

The Minexa.ai Personal plan is a $15 monthly floor, so at very small volumes a nano model costs less. GPT-5 nano on stripped HTML is $0.0024 a page, which crosses $15 at about 6,250 pages a month. GPT-4.1 nano and Gemini Flash Lite cross it at about 3,500.

On full HTML, GPT-5 nano passes $15 at around 520 pages.

Above those points, the gap grows with every page because LLM cost is linear in tokens and Minexa.ai cost is a flat plan.

• A one-off job of a few hundred stripped pages: a nano model is fine.
• A recurring pipeline in the thousands or more: Minexa.ai costs less at every volume tested.
• Any volume on full HTML: Minexa.ai, by 19× to over 1,000× at 10,000 pages.

Run the same comparison on your own HTML

If you already fetch pages with your own stack, proxies or another scraping API, you can compare like for like. Minexa.ai runs extraction only on HTML you've stored, at 1 credit per page.

1. Open one of your target pages in the Minexa.ai Chrome extension and create a scraper in List or Detail mode. The AI checks thousands of selector combinations and picks the most stable ones. This takes a few minutes, once.
2. Click API Request and choose the extract-only config for HTML you already have. The extension generates the exact request body for your scraper.
3. Put your stored HTML URLs in file_urls, the matching original pages in urls, and send it to the Minexa.ai API.

If you'd rather have the Minexa.ai API fetch pages too, pages that need JavaScript rendering, residential proxies or stronger anti-bot handling use more credits. That's fetching cost, which an LLM pipeline pays separately as well.

# POST https://api.minexa.ai/data/
# headers: {"Content-Type": "application/json", "api-key": "YOUR_KEY"}
{
  "scraping": {"js_render": false, "proxy": "verified"},
  "file_urls": [
    "https://9343.cloudfront.net/html-of-given-url-1.html",
    "https://9343.cloudfront.net/html-of-given-url-2.html"
  ],
  "urls": [
    "https://original-site.com/page-1",
    "https://original-site.com/page-2"
  ]
}

Each urls entry maps 1-to-1 to a file_urls entry so every extracted row traces back to its source page.