Context Window
Definition
The context window limits how much content a model can consider at the same time.
The context window is the model-dependent token capacity of a request. This includes inputs and outputs as well as internal reasoning tokens for corresponding models. It is not a permanent memory; large capacity does not guarantee error-free use.
Simply explained
Like the place on a desk: what does not fit in, is currently not available.
Why it matters in practice
Helps to realistically classify the possibilities, quality and limitations of AI systems.
Example from business
Possible example: A project team combines old parts of the conversation before working on new documents.
Limits and pitfalls
- Assume that a large context is automatically used correctly or remains permanently stored.
Origin & history
Current model APIs document model-dependent token limits for inputs, outputs and, where applicable, internal reasoning tokens. The context window is a limit per request and not a permanent memory.
Use in mid-sized companies
- Possible application in SMEs: A project team combines old parts of the conversation before working on new documents.
Frequently asked questions
What is Context Window (Context Window)?
The context window limits how much content a model can consider at the same time.
What errors should be avoided?
Assume that a large context is automatically used correctly or remains permanently stored.
Sources
- Conversation state / Context window · OpenAI, Conversation state / Context window
Sources checked on 10/09/2026. Editorial application examples are hypothetical; no evidence of real customer results.
Editorially reviewed on: