# Knowledge Cutoff

> A knowledge cutoff is the date a model's training data ends, so it has no built-in knowledge of any event, release, or fact that came after it.

**A knowledge cutoff is the date after which a model's training data ends, so the model has no inherent knowledge of any event, product release, or fact that came later.**

Ask about something newer than the cutoff and the model doesn't stay silent — it answers from stale or guessed information, often confidently. This is a common source of [hallucination](/glossary/hallucination): the model treats its frozen snapshot of the world as current, so it can report an old version number, a since-renamed library, or a price that has changed as if nothing moved.

The cutoff is not the model's release date. Training, evaluation, and safety work take months, so a model usually ships well after its data was frozen — meaning even a brand-new model is blind to the weeks or months just before it launched.

Apps work around this by feeding fresh information into the prompt rather than relying on what the model memorized. [Retrieval-augmented generation](/glossary/rag) pulls relevant documents from your own data, web-search or API tools fetch live facts, and you can simply paste current context in. The key idea is [grounding](/glossary/grounding): a model can "know" recent things only if you put them in front of it. For the retrieval pattern, see [how RAG works](/guides/concepts/how-rag-works).

---

_Source: https://agentscamp.com/glossary/knowledge-cutoff — Term on AgentsCamp._