Context Window Usage Calculator

What This Calculator Measures

Every AI model has a maximum context window — the total number of tokens it can consider in a single request, shared between your prompt/conversation history and its response. This calculator shows exactly how much of that budget your text uses, and how much room is left.

Why Context Window Fills Up Faster Than You'd Think

Long conversations accumulate tokens from every prior turn, not just the current message — most chat implementations resend the full conversation history with every new request unless they explicitly trim it. Pasted documents, retrieved search results, system prompts, and tool definitions all count against the same budget too.

The Math

% of context used = (tokens in your text ÷ model's context window) × 100
tokens remaining   = model's context window − tokens in your text
turns left (~)     = floor(tokens remaining ÷ average tokens per future turn)

What Happens Near the Limit

As a conversation approaches its context window, you'll typically see one of two things depending on how the client is built: the API rejects any request that would exceed the limit, or the client silently truncates older messages to make room — which can cause the model to "forget" earlier context without warning.

Common Mistakes

• Assuming a bigger context window means better recall. Models can still lose track of details buried in the middle of a very long context even when technically within the token limit — a large context window increases capacity, not necessarily attention quality.
• Forgetting output tokens share the same budget. A prompt that uses 95% of the context window leaves very little room for the model's response, and some APIs will simply fail the request rather than truncate the output.

Frequently Asked Questions