What is a context window?
A context window is the maximum amount of text (measured in tokens) that an AI model can process in a single interaction. It includes both the input prompt and the generated output. Understanding context windows is essential for effective prompt engineering.
Context Window Essentials
How context windows affect AI usage
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Token limits
Every AI model has a maximum context window — from 4K tokens for older models to 200K+ for newer ones. Both input and output count toward this limit.
Prompt budgeting
Allocate your context window wisely between system prompts, context, user input, and space for the model's response.
Information prioritization
When context is limited, prioritize the most relevant information and instructions in your prompts.
Attention degradation
Models may pay less attention to information in the middle of very long contexts — a known limitation called lost-in-the-middle.
Efficient prompting
Well-structured prompts use fewer tokens while conveying the same information, leaving more room for AI output.
Cost implications
Larger context windows cost more per interaction. Optimizing prompt length reduces costs at scale.
Benefits
Why context window awareness matters
FAQ
Frequently asked questions
What is the context window size for popular models?
GPT-4o supports 128K tokens, Claude 3.5 supports 200K tokens, and Gemini 1.5 supports up to 2M tokens. Larger windows allow more context but cost more per interaction.
How does TeamPrompt help with context windows?
TeamPrompt templates help teams write concise, efficient prompts that make the best use of available context. Shared templates eliminate verbose, duplicative prompting that wastes context window space.
Does the output count toward the context window?
Yes. The context window includes both input tokens (your prompt) and output tokens (the model's response). Plan your prompt length to leave adequate room for the response you need.
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