Knowledge Cutoff Date – Definition & Explanation

What is a Knowledge Cutoff Date?

The knowledge cutoff date is the point in time up to which a Large Language Model received data during its training. Events, information, or developments after this date are unknown to the model.

When you ask an AI model about current events that occurred after its cutoff, it will either honestly say it has no information – or it "hallucinates" an answer that sounds plausible but may be wrong.

Knowledge Cutoffs of Current Models

Here's an interactive overview of knowledge cutoff dates for over 80 current LLMs from OpenAI, Anthropic, Google, Meta, and other leading providers:

The table also shows the release date of each model. Interestingly, there's often several months between the knowledge cutoff and release – the time needed for training, fine-tuning, and safety testing.

Models with web access (marked with the globe icon) can access current information despite having an older knowledge cutoff.

Why Do Knowledge Cutoffs Exist?

Training is Intensive

Training an LLM takes months and costs millions. During this time, the training data is "frozen." The model cannot train and absorb new data simultaneously.

Data Curation Takes Time

Training data must be filtered, cleaned, and quality-checked. Additional months pass between collecting the data and completing training.

Quality Assurance

After training, extensive testing and fine-tuning processes follow before the model is released. This process can take additional months.

Dealing with the Knowledge Cutoff

Web Search and Tools

Modern AI assistants like ChatGPT with GPT-4 can retrieve current information via web search. This bypasses the knowledge cutoff for many use cases.

RAG (Retrieval-Augmented Generation)

Companies use RAG to provide LLMs with current or proprietary documents. The relevant information is inserted into the context window.

Continuous Training

Some providers regularly update their models with new training data. This shortens the period between cutoff and current events.

Practical Implications

• Current Events: Election results, sports events, news after the cutoff are unknown
• New Products: Current software versions or hardware may not be known
• Science: Latest research findings are missing
• Legal: Law changes after the cutoff not considered

Asking About the Knowledge Cutoff

You can directly ask an AI model about its knowledge status: "What is your knowledge cutoff date?" Reputable models will answer honestly. When in doubt, you should always verify critical facts.

Conclusion

The knowledge cutoff is a fundamental property of current LLMs. It means that AI models don't have "living" knowledge but a snapshot of the world at a specific point in time. For time-sensitive information, you should always consult current sources or use models with web access.