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Home/Concepts/Knowledge Cutoff
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FundamentalsBeginner

Knowledge Cutoff

The date after which an AI model has no training data — and doesn't know what happened.

Every LLM has a knowledge cutoff — the date at which its training data collection ended. The model has no information about events, publications, prices, or code updates that occurred after this date.

Practical implications:

  • Ask about a recent event → the model may confabulate (hallucinate) or say it doesn't know
  • Ask for today's date → the model doesn't know (unless told via system prompt)
  • API pricing, library versions, political situations → likely outdated

How to work around it:

  1. Tell the model today's date in the system prompt — it can then adjust its answers accordingly
  2. Use RAG to inject current documents before the model answers
  3. Use models with web search (Perplexity, ChatGPT with browsing, Claude with search tools)
  4. Build time context in — paste the relevant current information directly into the prompt

Common cutoff dates:

  • Claude 3.5 Sonnet: April 2024
  • GPT-4o: October 2023
  • Claude Sonnet 4.6: August 2025
  • Always verify at the provider's docs — cutoffs are updated with new model versions.

In plain terms

A brilliant researcher who went into isolation in April 2024 and has been completely offline since. Extraordinarily knowledgeable — but genuinely unaware of anything that happened after that date.

Related concepts

⬡

Large Language Model

AI trained on vast text to understand and generate language.

📚

Retrieval-Augmented Generation

Giving the AI access to your documents before it answers.

👁️

Hallucination

When an AI generates confident-sounding facts that are simply wrong.

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