Context Windows Quiz

Answers and explanations appear as you take the quiz.

1. What does a model's context window measure?
   • The screen resolution of the chat interface
   • The maximum amount of text, in tokens, the model can consider at once
   • How many users can chat at the same time
   • The model's total training dataset size
2. How should a token be interpreted when budgeting language-model context?
   • As exactly one full word in every language
   • As exactly one sentence in every tokenizer
   • As a tokenizer-defined unit whose relation to words depends on the model and text
   • As the API password used to send a request
3. In a decoder-style request with a shared input-and-continuation budget, which supplied material uses that budget?
   • Instructions, conversation turns, document tokens, and the generated continuation
   • Only the latest user message
   • Only stored application files that were never supplied
   • Only generated output, with input always free
4. Under a dense full-attention pairwise-interaction model, how does comparison count scale when a request's token length doubles?
   • It becomes only twice as large under that model
   • It stays unchanged regardless of length
   • It becomes half as large
   • It becomes four times as large under the quadratic model
5. The 'lost in the middle' problem refers to models tending to:
   • Crash whenever the input is long
   • Translate the middle of a document into another language
   • Recall information at the start and end of a long input better than the middle
   • Ignore the first and last sentences entirely
6. Why can retrieval be combined with a language model's limited context window?
   • It guarantees the lowest total cost for every workflow
   • It selects passages to supply rather than requiring the whole knowledge base as input
   • It permanently increases the model's supported token capacity
   • It removes the need to evaluate generated answers
7. In an illustrative shared context budget of 8,000 tokens, input uses 6,500. How many tokens remain before other limits or overhead?
   • 6,500
   • 8,000
   • 14,500
   • 1,500
8. What can happen when an input exceeds a language model interface's supported context?
   • Rejection, truncation, or application-side shortening, depending on the setup
   • Automatic permanent memory of all excluded text
   • Guaranteed silent deletion of the oldest message in every system
   • Automatic expansion of every model's trained architecture