What is a context window?

A context window is the maximum number of tokens an AI model can process in a single request, including the system prompt, user messages, and the generated response. Exceeding this limit causes the model to truncate or reject your input.

How do I reduce context window usage?

Shorten your system prompt by removing redundant instructions, truncate long user inputs, or switch to a model with a larger context window such as Claude (200K) or Gemini 1.5 Pro (2M tokens).

Are token counts exact?

Token counts are approximate — they use a word-based heuristic (~1.3 tokens per word). For exact counts use the official tokenizer libraries such as tiktoken for OpenAI or the Anthropic token counting API.

AI Context Window Calculator

Check if your prompts fit within any AI model context window.

Model

System prompt

User prompt

Expected output tokensMax output for GPT-4o: 4,096 tokens

Total context usage

5000.4% of 128.0K

System tokens0

User tokens0

Output tokens500

Remaining127,500

Related Tools

TKNAI Token CounterNEW

Count tokens for GPT, Claude, Gemini, and LLaMA models.

CSTAI API Cost CalculatorNEW

Estimate AI API costs for GPT, Claude, Gemini, and LLaMA.

GPTOpenAI Context Window CalculatorNEW

Check if your prompts fit within GPT-4o and GPT-3.5 context windows.

CLDClaude Context Window CalculatorNEW

Calculate token usage against Claude 200K context windows.

Learn More

guide:context window management guide:chunking strategies

FAQ

What is a context window?: A context window is the maximum number of tokens an AI model can process in a single request, including the system prompt, user messages, and the generated response. Exceeding this limit causes the model to truncate or reject your input.
How do I reduce context window usage?: Shorten your system prompt by removing redundant instructions, truncate long user inputs, or switch to a model with a larger context window such as Claude (200K) or Gemini 1.5 Pro (2M tokens).
Are token counts exact?: Token counts are approximate — they use a word-based heuristic (~1.3 tokens per word). For exact counts use the official tokenizer libraries such as tiktoken for OpenAI or the Anthropic token counting API.

Calculate context window usage for GPT, Claude, Gemini, and LLaMA models. Enter system and user prompts, set expected output tokens, and instantly see if you are within limits. Token counts are approximate using word-based heuristics.