The knowledge cutoff is the point in time up to which a language model has been trained on data. Events and content after that date are unknown to the model unless it can reach current sources.
What does the cutoff mean in practice?
A model’s knowledge does not change after training. Questions about later events get no answer or an outdated one. Wikipedia separates the stated cutoff, the official end of the training data, from the effective cutoff, the date up to which the model’s knowledge is actually reliable. According to Wikipedia, the effective cutoff often differs by subject.
Some vendors publish two values. Anthropic lists a “reliable knowledge cutoff”, the period in which the model’s knowledge is most extensive and reliable, and a “training data cutoff” for the broader data used. Claude Haiku 4.5 has a reliable cutoff of February 2025 and a training data cutoff of July 2025. Claude Sonnet 5.5 lists June 2026 for both (as of October 2026).
How do AI systems work around it?
They add web search or retrieval-augmented generation (RAG), so the model reads current documents before it answers. Wikipedia also mentions incremental updates such as fine-tuning, which carry the risk of the model forgetting earlier knowledge.
What does it mean for SEO and AI search?
Content published after the cutoff can only appear in an answer through live retrieval, not through the model’s built-in knowledge (assessment). For new pages, this makes it relevant whether bots can reach and read them.
Example
A model with a cutoff of February 2025 gets a question in October 2026 about a Google update from the summer of 2026. Without web search it has nothing reliable to say. With web search it reads current sources and answers from those.
FAQ
What is ChatGPT’s knowledge cutoff? It depends on the model. The vendor’s model documentation is the reliable place to look, because the value changes with each version.
How do you get around the cutoff? With web search, retrieval from your own knowledge base, or by pasting current documents into the prompt.
Sources
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