Should you publish your content as a PDF or stick strictly to standard HTML? Does Google treat PDF files differently when it comes to indexing, ranking, and AI search features? In this episode of Search Off the Record, Martin Splitt and John Mueller from the Google Search Relations team demystify how Google Search handles PDF documents. They break down some of Google's internal pipelines, explain why putting an LLMs.txt file inside a PDF is a bad idea, explore common technical traps like rasterized pages and canonicalization issues, and share practical advice on managing PDFs for SEO, AEO (SEO), and user experience. In this episode, you'll learn: Google's PDF converter pipeline: How Google converts binary PDF containers into HTML pages during indexing so the rest of the pipeline can process them normally. LLMs.txt as a PDF: Why saving an LLMs.txt file as a PDF is a bad idea, even if you like LLMs.txt. File limits & Project Gutenberg: Why crawling limits exist, and how HTML and PDF size limits function in the crawl pipeline. Rasterized pages & accessibility: How pages saved as images destroy text readability, ruin screen reader accessibility, and prevent Google from extracting text content. Canonicalization & "binary blobs": Why identical PDF downloads across different sites make canonicalization harder and how using rel="canonical" HTTP headers or embedded header links can help. PDFs for SEO in AI Overviews: How PDFs are parsed, ranked, and referenced in Google Search, AI Overviews, and broader AI systems for training and grounding. Key takeaways for SEOs & developers: HTML is preferred, and PDFs work: HTML offers better mobile responsiveness, zoom reflow, and faster loading. Internally, Google converts indexable PDF text into HTML so they can rank normally and appear in AI features. Test for text indexability: Highlight and copy text out of your PDF into a text editor; if text doesn't copy, it might be a rasterized image and can't be indexed easily. For restaurant menus: A PDF menu is better than no menu at all for restaurants, but a responsive HTML web page provides superior performance, accessibility, and user experience. Chapters 00:00 – Introduction: Welcome and setting the stage for PDF discussion. 00:50 – Can you save an LLMs.txt file as a PDF? 01:56 – Plain text vs. Binary container: What makes PDFs different from HTML? 03:08 – Inside Google's converter pipeline: Turning PDFs into HTML for indexing. 05:08 – Extracting images and links from PDF files. 06:04 – Crawling limits, file sizes, and testing cut-off thresholds. 08:35 – When does it make sense to publish a PDF? 09:33 – Do PDFs rank in Search, AI Overviews, and AI mode? 11:22 – Technical pitfalls: Rasterized pages, scanned images, and accessibility. 12:53 – Mobile connection delays, layout locking, and zoom issues. 14:12 – Canonicalization challenges with duplicate "binary blobs". 15:57 – Metadata, password protection, and updating PDF files. 18:59 – The problem with dynamic CMS PDF generation. 21:08 – The restaurant menu debate: PDF vs. HTML web pages. 23:00 – PDFs for GEO (Generative Engine Optimization) & AI grounding. 24:14 – Outro and community question. Resources Mentioned: Official Google Search Central Documentation: https://developers.google.com/search Google Search Console: https://search.google.com/search-console Don't forget to like and subscribe to the podcast on your favorite platform to catch every behind-the-scenes episode from the Search Relations team! Episode transcript → https://goo.gle/sotr115-transcript Listen to more Search Off the Record → https://goo.gle/sotr-yt Subscribe to Google Search Channel → https://goo.gle/SearchCentral Search Off the Record is a podcast series that takes you behind the scenes of Google Search with the Search Relations team. #SOTRpodcast #SEO #GoogleSearch #TechnicalSEO #GenerativeEngineOptimization Speakers: Martin Splitt, John Mueller
