Context Window Checker
Check if your text fits within the context window of popular AI models. Paste your prompt and see which models can handle it.
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How to use this calculator
Tokens are estimated at 1 token per 4 characters. The reserved output buffer is subtracted from each model's context window to determine if your input will fit while leaving room for the response.
- 1
Paste your full prompt or document text into the text area.
- 2
Set the number of tokens you want to reserve for the model's output (default: 2,000).
- 3
Read the table to see which models can handle your input and what percentage of each context window you are using.
Frequently asked questions
What does "reserve tokens for output" mean?
The context window is shared between your input and the model's response. If your prompt uses 95% of the window, the model can only generate a very short reply. Reserving tokens (e.g., 2,000) ensures there is space for a meaningful response.
Why does Llama 3 (70B) have a small context window?
The 8,192-token figure reflects the base Llama 3 release. Some fine-tuned or quantized variants support larger windows. Check the specific model card for the deployment you are using, as context limits vary widely by provider and configuration.
Is token estimation accurate for non-English text?
The 4-characters-per-token estimate is calibrated for English. Languages with non-Latin scripts (Chinese, Japanese, Arabic, etc.) often require 1–2 tokens per character, meaning the same number of characters produces far more tokens. For non-English content, assume your token count could be 2–4× higher.
Context Window Checker — See Which AI Models Fit Your Prompt
Why context window size matters
Every AI model has a maximum context window — the total number of tokens it can process in a single request. Exceed it and the API returns an error or silently truncates your input. Knowing which models can handle your content before making an API call saves debugging time and prevents silent data loss in production applications.
Comparing model context windows in 2024
Context window sizes span three orders of magnitude across popular models. Llama 3's base models top out at 8,192 tokens — enough for a few pages. GPT-4 Turbo and Claude 3 extend to 128,000–200,000 tokens, covering books and long codebases. Gemini 1.5 Pro's 1,000,000-token window is the current public frontier, capable of processing entire novels or large codebases in a single call.
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Results are estimates for informational purposes only and do not constitute professional financial, medical, legal, or technical advice. Read full disclaimer →