AI Prompt Length Checker

What is AI Prompt Length Checker?

Every LLM has a fixed context window — the maximum number of tokens it can process in a single call, including both the prompt and the response. If your prompt is too long, the API will return an error or silently truncate older messages in a conversation. It is important to reserve tokens for the response: a 128k context window with a 127k-token prompt leaves only 1k tokens for the model to answer — far too little for most tasks. This tool helps you measure your prompt against the model's limit before you hit the API.

How to use this tool

1. 1 Select your target model from the dropdown and set how many tokens to reserve for the response (500–2000 is typical; longer outputs need more headroom).
2. 2 Paste the complete prompt — system instructions, retrieved context, conversation history, and user message combined — exactly as it would be sent to the API.
3. 3 Read the status banner: green means it fits comfortably, amber means you are running tight, red means it will cause an API error or truncation.
4. 4 Use the stacked bar to visualise prompt tokens, reserved output tokens, and remaining free space — making the trade-off between prompt length and response headroom immediately visible.

When would you use this?

• Developers building RAG pipelines ensuring retrieved chunks + system prompt + user question fit within the window before calling the API.
• Prompt engineers testing very long system instructions to avoid context overflow errors.
• Teams migrating from one model to another (e.g. GPT-4o to Claude) checking that existing prompts fit within the new model's window.
• Anyone leaving headroom for a long response using the reserved-output slider.

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