Calculate how much of an AI model's context window your prompts use. Plan token budgets for GPT-4, Claude, Gemini and compare capacity across models.
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LLM context windows determine how much information you can include in a single prompt. Our Context Window Calculator helps you plan token budgets, visualize usage, and compare capacity across GPT-4, Claude, Gemini, and other models.
A context window is the maximum number of tokens an LLM can process in a single request—including your prompt and the model's response. GPT-4o has 128K tokens, Claude 3 has 200K, and Gemini 1.5 Pro leads with 1M tokens. Exceeding the limit causes truncation or errors.
Context Usage Formula
Available Tokens = Context Window - System Prompt - User Input - Expected OutputExceeding the context window causes your prompt or response to be cut off, losing critical information. Calculate usage before sending expensive API calls.
System prompts persist across conversation turns, eating into available space. Plan your token budget to leave room for user input and responses.
Small context windows (8K-32K) suit simple queries. Long documents and code analysis need 128K+. RAG applications may require Gemini's 1M context.
Larger context windows often mean higher costs. Use the minimum context size that fits your use case to minimize API expenses.
The API will either return an error, truncate your input from the beginning, or truncate the response. This can cause loss of critical context, broken code, or incomplete answers. Always leave a safety buffer.
A rough rule: 1 token ≈ 4 characters in English, or about 0.75 words. A page of text is ~750 tokens. Code typically has more tokens per line due to symbols. Use our Token Count Calculator for precision.
No. Larger contexts cost more and may slow responses. Performance can degrade on very long prompts. Use the smallest context that fits your task. Gemini's 1M context is powerful but expensive—reserve it for truly long documents.
It depends on your task. Chat responses: 500-1000 tokens. Code generation: 1000-2000 tokens. Long-form content: 2000-4000 tokens. Always check the model's max output limit—GPT-4 Turbo caps at 4096 tokens regardless of context.
System prompts often include instructions, examples, and formatting rules. Each word and symbol costs tokens. Condense instructions, remove redundancy, and consider if all examples are necessary. A lean system prompt leaves more room for user content.