LLM Context Window Calculator
See if your system, context and user messages fit the model window.
Messages
Context budget
Estimating while the tokenizer loads
Fits — 126,962 tokens left after reserving 1,024 for the reply.
Same prompt on other models
- GPT-4o0.0% of 128,000
- GPT-4o mini0.0% of 128,000
- GPT-4.10.0% of 1,047,576
- GPT-4.1 mini0.0% of 1,047,576
- o30.0% of 200,000
- GPT-4 Turbo0.0% of 128,000
- GPT-3.5 Turbo0.1% of 16,385
- Claude Sonnet0.0% of 200,000
- Claude Haiku0.0% of 200,000
- Claude Opus0.0% of 200,000
- Gemini Flash0.0% of 1,048,576
- Gemini Pro0.0% of 1,048,576
- Llama 3.3 70B0.0% of 128,000
- Mistral Large0.0% of 131,072
About the LLM Context Window Calculator
Break a request into system prompt, retrieved context and user message, add realistic chat overhead, reserve room for the reply and instantly see whether the request fits GPT, Claude, Gemini, Llama or Mistral context windows.
Examples
RAG request
system + 8 chunks + questionOutput
12,480 / 128,000 tokens — fitsKeyboard shortcuts
- Copy the main outputCtrl / ⌘ + Shift + C
- Download the resultCtrl / ⌘ + S
- Share this toolCtrl / ⌘ + Shift + S
- Reset the inputsAlt + R
- Open the tool search paletteCtrl / ⌘ + K
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Frequently asked questions
Read more
- How LLM tokens really work (and why your word count is a bad estimate)
BPE splits words, punctuation and whitespace into pieces. Here is how tokens are counted, why context windows overflow, and how to plan a prompt that fits.
Version 1.0.0 · Updated 2026-08-14 · Runs entirely in your browser