AI 引擎在回答 LLM 网关问题时实际引用了什么

What AI engines actually cite when you ask about LLM gateways 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. What we did The 27 questions are the ones a developer actually types, not what a keyword tool suggests: What are the best OpenRouter alternatives? Is it safe to route API calls through a third-party LLM gateway? Are free LLM APIs reliable enough for real work? How do I point Claude Code at a different API base URL? 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 346 unique domains. 1. No single source dominates 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. 2. The head still has a shape 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. 3. Reddit barely appears 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. 4. Where YouTube appears, it is someone else's tutorial 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. What we took away from it 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. Limits 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. Disclosure 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/