What AI engines actually cite when you ask about LLM gateways

A developer behind FreeModel ran 27 developer-style questions through four AI engines on a single day and analyzed the 613 citations returned, finding that the ten most-cited domains account for only 18.6% of citations while 81% spread across 336 domains. The study found GitHub lists and issue threads, first-person dev.to tutorials with numbers, and competitor pricing, privacy, and sub-processor pages were cited directly, while Reddit accounted for just 0.5% of citations. Only Perplexity, accessed via OpenRouter, exposed its sources, so the other three engines were excluded from the dataset.

We wrote 27 questions the way a developer asks them, sent them to four engines on one day, and counted where the citations pointed. Here is the distribution — including the findings that argue against our own product strategy. The 27 questions are the ones a developer actually types, not what a keyword tool suggests: Each question went to four engines on 2026-09-20 . Only one of them returns the sources its answer was built from — Perplexity, reached through OpenRouter. An answer with no citation trail cannot be measured, so the other three engines are not in this dataset at all. What is left: 613 citation entries across the 27 answers, collapsing to 569 unique URLs and The ten most-cited domains account for 18.6% of all citations. The remaining 81% spreads across 336 domains, and most of those appear exactly once. This is worth stating plainly, because the standard advice in this space — get into the big awesome list and you are done — does not survive contact with the data. There is no list to win. There is a long tail, and each entry in it is a small bet. | Domain | Citations | What the cited pages actually are | |---|---|---| | github.com | 17 | Awesome lists, tool repositories, and issue threads | | dev.to | 17 | Long-form tutorials and comparisons, first person | | openrouter.ai | 15 | A competitor's own product and pricing pages | | llmgateway.io | 15 | Comparison blog posts, pricing, and legal pages | | startupfortune.com | 11 | News coverage and tag archives | | marktechpost.com | 10 | Category index pages | | youtube.com | 9 | Tutorial videos | | reddit.com | 3 | Discussion threads | The GitHub entries are not documentation. They are lists — directories of free APIs and gateways — and issue threads , where someone asks how to change the base URL in Claude Code or Cline and other people answer. Both are places where a project can be named without writing a blog post. The dev.to entries are all first-person and all contain numbers. Not one of them is a product announcement. And competitor marketing pages get cited directly — including, for the question about whether a gateway can read your prompts, a competitor's privacy policy and sub-processor list. Those pages are usually written for lawyers. They are being read as answers. Three citations out of 613 — 0.5% — went to reddit.com. That one deserves a pause, because "Reddit shows up in 40% of AI answers" is repeated everywhere. The figure is real. It is also averaged across every topic imaginable. For developer tooling questions, the engines reached for repositories and tutorials instead. If you were about to spend this quarter on Reddit, the data says spend it elsewhere — for this category, at least. All nine YouTube citations are setup tutorials, and eight of them are about one competitor, by name, walking through a configuration the viewer could copy. Publish where the engines already read. For this category that is repositories, issue threads, and long-form tutorial posts — not launch announcements. Your boring pages are answer pages. Pricing, terms, privacy, and sub-processor lists answer real questions that people ask engines. One competitor collected four citations from legal pages in a single question. Expect the long tail. 81% of citations spread across 336 domains. There is no single placement that fixes visibility, which also means no single competitor can lock it up. One engine. One day. 27 questions, all of them ours, chosen to cover what we care about. A different question set or a different date would produce a different distribution. Three of the four engines returned no citations at all because they do not expose them — so this study says nothing about how those three answer, only about which one is measurable. Treat it as a snapshot, not a trend. We operate FreeModel, and our product is one of the things these 27 questions ask about. In this round it received zero citations . Every competitor named above was cited more often than we were. We are publishing the method and the distribution rather than a conclusion, because the number that matters is the one you can re-run. The full write-up, with the same numbers, is on our site: https://freemodel.online/compare/ai-citation-study/ https://freemodel.online/compare/ai-citation-study/