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What Is a Context Window in LLMs — LLM Guides
Context windows in LLMs define the maximum amount of text, measured in tokens, that a model can process in a single conversation turn, including both input and output. The article explains how context windows work, why they exist due to self-attention computational costs, and how they have grown from 4,096 tokens in 2020 to up to 1 million tokens in 2026.
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Summary
Context windows in LLMs define the maximum amount of text, measured in tokens, that a model can process in a single conversation turn, including both input and output. The article explains how context windows work, why they exist due to self-attention computational costs, and how they have grown from 4,096 tokens in 2020 to up to 1 million tokens in 2026.
Tags
context-window · llm · tokens · large-language-models · self-attention · ai-fundamentals · prompt-engineering
Key entities
Context Window (concept, 0.99) · Self-Attention (concept, 0.9) · Tokens (concept, 0.92) · GPT-3 (technology, 0.95) · GPT-4 Turbo (technology, 0.9) · Claude Opus 4.6 (technology, 0.88) · Stojan (person, 0.75) · Large Language Models (concept, 0.97) · Sparse Attention (concept, 0.8) · OpenAI (organization, 0.7)
Classification
reference · language en · status final
Provenance
claude-opus-4-6 via @stacklist/mcp-server@2.0.0, confidence 0.85, 2 Jul 2026