# Knowledge cutoff

Category: [AI Search & GEO](https://seo-geo-glossary.com/en/glossary/category/ai-search-geo/) › [AI & LLM basics](https://seo-geo-glossary.com/en/glossary/category/ai-search-geo/ai-llm-basics/)

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 Questions about later events get no answer or an outdated one.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.

## Related terms

- [Large language model (LLM)](https://seo-geo-glossary.com/en/glossary/large-language-model/index.md)
- [Training data](https://seo-geo-glossary.com/en/glossary/training-data/index.md)
- [Retrieval-augmented generation (RAG)](https://seo-geo-glossary.com/en/glossary/retrieval-augmented-generation/index.md)
- [Grounding with Google Search](https://seo-geo-glossary.com/en/glossary/grounding-with-google-search/index.md)
- [AI hallucination](https://seo-geo-glossary.com/en/glossary/ai-hallucination/index.md)
- [Context window](https://seo-geo-glossary.com/en/glossary/context-window/index.md)

## Sources

- [Models overview (reliable knowledge cutoff, training data cutoff) - Claude Platform Docs](https://platform.claude.com/docs/en/about-claude/models/overview)
- [Knowledge cutoff - Wikipedia (secondary source)](https://en.wikipedia.org/wiki/Knowledge_cutoff)
- [What is an AI knowledge cutoff? - Conductor Academy (secondary source)](https://www.conductor.com/academy/ai-knowledge-cutoff/)

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Last updated: October 7, 2026
URL: https://seo-geo-glossary.com/en/glossary/knowledge-cutoff/