12 Jan 2026·Source: The Hindu

4 min

Science & TechnologyEXPLAINED

AI Context Window: Understanding Short-Term Memory in Large Language Models

Context window defines the amount of text an AI model can process.

Photo by Igor Omilaev

Background Context

Early AI models had very limited context windows, leading to disjointed conversations.

Why It Matters Now

Larger context windows are enabling more sophisticated AI applications.

Key Takeaways

•Context window: AI's short-term memory
•Tokens: Chunks of characters AI reads
•Larger window: More data, more power
•Lost in the middle: Info retrieval issue

Related Concepts

Large Language Models Tokenization AI Memory Computational Resources

The article explains the concept of the context window in artificial intelligence (AI), particularly in large language models (LLMs) like GPT-5 and Claude. The context window refers to the maximum amount of text an AI model can consider at one time while generating a response. AI models read chunks of characters called tokens, where one token is roughly equivalent to 0.75 words.

For example, a model with an 8,000-token context window can handle about 6,000 words at once. The context window needs to hold the rules for AI behavior, the history of the current chat, and the space required for the AI to generate its next answer. If a conversation exceeds the context window, the model might start deleting the oldest parts of the conversation.

Increasing the context window length requires more computational resources. Even with a large context window, AI models may struggle to find information buried in the middle, a phenomenon called the 'lost in the middle' phenomenon.

Key Facts

Context window: Max text AI model can consider

1 token ≈ 0.75 words (English)

Larger context window: More computational resources needed

UPSC Exam Angles

GS 3: Science and Technology - Developments and their applications and effects in everyday life

GS 2: Governance, Constitution, Polity, Social Justice and International relations - AI ethics and governance

Potential question types: Statement-based MCQs on AI capabilities, analytical questions on the impact of AI on society

Visual Insights

Practice Questions (MCQs)

1. Consider the following statements regarding the 'context window' in Large Language Models (LLMs): 1. It refers to the maximum amount of text an AI model can consider at one time while generating a response. 2. Increasing the context window length invariably improves the accuracy of information retrieval from any part of the text. 3. The 'lost in the middle' phenomenon suggests that LLMs may struggle to find information buried in the middle of a large context window. Which of the statements given above is/are correct?

A.1 and 2 only
B.1 and 3 only
C.2 and 3 only
D.1, 2 and 3

Show Answer

Answer: B

Statement 1 is correct as it defines the context window. Statement 3 is correct as it describes the 'lost in the middle' phenomenon. Statement 2 is incorrect because increasing the context window doesn't guarantee improved accuracy due to the 'lost in the middle' issue.

2. Which of the following statements best describes the function of 'tokens' in the context of Large Language Models (LLMs)?

A.They are the fundamental units of data storage in LLMs, representing individual files.
B.They are the smallest units of text that an LLM processes, typically representing words or parts of words.
C.They are the mathematical representations of concepts used for semantic analysis.
D.They are the parameters that control the learning rate of the LLM during training.

Show Answer

Answer: B

Tokens are the basic building blocks of text that LLMs process. They can be whole words, parts of words, or even individual characters, depending on the tokenization method used.

3. Assertion (A): Increasing the context window size in Large Language Models (LLMs) always leads to better performance in complex reasoning tasks. Reason (R): A larger context window allows the LLM to consider more information, but it also increases the computational cost and can lead to the 'lost in the middle' phenomenon. In the context of the above statements, which of the following is correct?

A.Both A and R are true, and R is the correct explanation of A.
B.Both A and R are true, but R is NOT the correct explanation of A.
C.A is true, but R is false.
D.A is false, but R is true.

Show Answer

Answer: D

Assertion A is false because increasing the context window size doesn't always guarantee better performance due to the 'lost in the middle' phenomenon and increased computational cost. Reason R is true as it accurately describes the trade-offs associated with larger context windows.