LLM Context Window Checker
Estimate tokens and see how your text fits in GPT-4o, Claude, Gemini and more
About LLM Context Window Checker
Estimates how many tokens your text uses and shows what share of the context window it fills for popular models from OpenAI, Anthropic, Google, Meta and Mistral, with a colored bar per model and an EXCEEDS flag past 100%. The estimate is characters divided by four, applied to every model, rather than a real tokenizer, so treat it as a quick fit check.
Category: AI Tools.
Frequently asked questions
What is a context window?
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The maximum number of tokens a model can process in a single request, including both the prompt (input) and the generated response (output). Exceeding it causes an API error or silent truncation.
How accurate is the token count?
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It's a rough estimate: the tool divides the number of characters by four, rounds up and uses that same figure for every model instead of each provider's tokenizer. That works reasonably for plain English, but code, other languages and especially Chinese, Japanese or Korean text can need far more tokens than shown.
What happens if I exceed the context window?
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APIs usually reject the request with an error, while chat apps may drop or summarize older messages to make room. The model's reply also counts toward the limit, and this checker compares only your text against the full window, so keep a margin below 100% for the output.
Are the context limits up to date?
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They are a fixed snapshot stored in the page, not fetched from each provider, so newer models or recently expanded limits may be missing. Check the provider's documentation before relying on an exact limit, especially for long-context models.