My AI tools directory (aiappdex.com) launched with individual model pages — one page per HuggingFace model, with download counts, tags, and Claude-generated pros and cons. That's a minimum viable directory. But directory users don't only search for a model by name; they search for two models side by side. "Llama 3 vs Mistral 7B for a local inference project." "Which text-classification checkpoint fits my fine-tuning budget." Comparison pages serve a different intent than detail pages, and I built a pipeline to generate them at scale.
This is how the pipeline works, what its failure modes are, and what I'd change if I were starting over.
Why comparison pages at all
The argument for comparison pages is search intent. A user who types "[model A] vs [model B]" is further along in an evaluation than one who types "[model A]." They already know which models they're considering; they want a structured side-by-side. That's a more specific intent signal.
The argument against auto-generating them is quality. If I ask Claude to compare two models it knows nothing concrete about and produce a paragraph of accurate-sounding generalities, I'm not adding value — I'm producing plausible boilerplate. The prompting had to produce content specific enough to be useful, or at least honest enough not to actively mislead.
