What is Context Window?
A context window is the maximum number of tokens an LLM can process. Learn about context limits and how claw.zip compression extends them for OpenClaw users.
Definition
Context Window
A context window is the maximum number of tokens a large language model can process in a single request, including both the input prompt and the generated output. It defines the upper limit of information you can provide to the model in one interaction.
Why It Matters
Why You Should Care
Context windows limit how much information you can include in a prompt. Long documents, conversation histories, and detailed instructions can exceed these limits, forcing you to truncate information and potentially lose important context. For OpenClaw users, prompt compression helps fit more meaningful content within the same window.
How It Works
Under the Hood
Each model has a fixed context window size (e.g., 200K tokens for Claude). Your input prompt and the model's output must fit within this window. If your prompt is too large, you must either truncate it, split it across multiple requests, or compress it. claw.zip compression can effectively extend your usable context window by fitting more information into fewer tokens.
Related Terms
Keep Learning
Token Counting
Token counting measures how many tokens are in a prompt or response. Learn why token counts matter for OpenClaw API costs and context windows.
Prompt Compression
Prompt compression reduces the number of tokens in AI prompts while preserving meaning. Learn how it works and why it matters for OpenClaw API costs.
LLM API Costs
LLM APIs charge per token for input and output. Learn how pricing works, what drives OpenClaw costs, and how to reduce AI API spend by 80-93%.
Semantic Compression
Semantic compression reduces tokens while preserving meaning. Learn how it differs from basic text compression and why it is better for AI.
See Context Window in Action
Try claw.zip free and experience the difference for yourself.