How reference and document lengths affect Copilot responses
Applies To
Last updated: April 2026​​​​​​​
Note: This article was partially created with the help of AI. An author reviewed and revised the content as needed. Read more about Microsoft and Responsible AI practices.
When you write Copilot prompts, you can provide Copilot with information or samples - the source for Copilot to use. For example, you can ask Copilot in Word: Write a marketing plan outline based on the product features described in this document. But to get the best output from Copilot, it's important to consider the length of the content you provide to Copilot.
Depending on the type of tasks you give Copilot, there are times that Copilot will focus only on the beginning of the document and then ignore anything beyond that. For example, when you ask a question about a specific topic in a long document, document length typically will not impact the ability to get a result based on how the Large Language Models (LLMs) reason over the content. But if you ask for a summary of a long document, the task requires the entire document context to inform the output.Â
Tips for Longer Documents
Here are some ways that you can use longer documents more effectively with Copilot:
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Break It Down: If you have a long document, consider splitting it into smaller documents and providing them to Copilot separately. This way, Copilot can handle each part effectively.
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Summarize in Parts: For long reports or manuscripts, you can try summarizing them in chunks with Copilot. Today you can do that by copying/pasting chunks into separate documents and summarizing sections separately. This helps Copilot to give you more precise and relevant responses.
When using Copilot, think of it as having a conversation with your friend. You wouldn't discuss a whole encyclopedia at once, right? Similarly, keep your document references concise and to the point for the best experience with Copilot.
Notes:Â
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You may need to adjust the size of the document based on the language you use.
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Large language models (LLMs) tend to prioritize content that is at the beginning and end of a file. Accordingly, the results you get may give less attention to content that was in the middle of a long file.
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We are working on functionality that allows you to point Copilot to a specific section or page range in a document.
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