AI Glossary
Model Context Window
The maximum amount of text an AI model can process in a single interaction. Larger context windows (100K+ tokens) enable processing of long documents, codebases, or conversation histories.
Understanding Model Context Window
The context window determines how much information you can feed an AI model in a single interaction. Early models had 4K token windows (roughly 3,000 words). Today's models offer 128K-200K tokens, with some reaching 1M+ tokens.
For businesses, larger context windows unlock new use cases: analyzing entire contracts, processing full quarterly reports, reviewing complete codebases, or maintaining long conversation histories without losing context.
However, larger isn't always better. Processing more tokens costs more money and takes more time. Effective AI implementations use RAG to retrieve only the relevant sections rather than stuffing the entire knowledge base into every query.
Model Context Window in Canada
For Canadian businesses handling bilingual documentation, context window size is especially important as English/French translations effectively double the text length that needs processing.
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Frequently Asked Questions
A one-page document is roughly 500 tokens. A 50-page contract is about 25,000 tokens. A full annual report might be 100,000-200,000 tokens. Most modern models can handle these in a single interaction.
No. Larger inputs cost more and can dilute the model's attention. Use RAG to retrieve relevant sections rather than processing entire documents when possible.
See Model Context Window in Action
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