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LLM Prompt Token Length Calculator

Every large language model has a context window measured in tokens (e.g., 8K for GPT-3.5, 128K for GPT-4 Turbo, 200K for Claude 3.5, 1M for Gemini 1.5 Pro). If your prompt exceeds this limit, the API truncates the input or refuses the request entirely. This calculator checks whether your prompt fits within your target model's context window after accounting for an output token offset. Paste your full prompt (system instructions, examples, user message), select your model, and specify how many tokens to reserve for the response. The calculation uses a 0.75 character-to-token ratio calibrated to the cl100k_base algorithm (accurate for GPT-4/Claude/Gemini tokenizers) and displays a visual progress bar with safe/warning/error zones. Use it before hitting Submit to avoid wasted calls, incomplete context, or silent truncation. Free, client-side validation with no data sent to external servers.

How to Use This Tool

  1. Select your target model from the dropdown to load its context limit (8K to 1M tokens).
  2. Set output reserve in the number input (default 1,000 tokens) for model response space.
  3. Paste your full prompt into the text area, including system instructions and examples.
  4. View real-time validation showing prompt tokens, max allowed tokens, and usage percentage.
  5. Check the status card for safe (green), near-limit (yellow), or exceeds-limit (red) warnings.
  6. Reduce prompt size if needed by removing examples, shortening instructions, or splitting requests.

Why Use This Tool?

Context windows are hard limits enforced at the tokenization layer. GPT-4 Turbo's 128K-token window holds roughly 96,000 words of plain English, but code, JSON, or non-English text can reduce this by 30-50%. If you send a 130K-token prompt to a 128K-token model, the API returns an error (OpenAI) or silently truncates the oldest messages (some chat implementations). Reserving output tokens is critical because the context window includes both input and output. A 128K model with a 120K-token prompt can only generate 8K tokens before hitting the ceiling, causing incomplete responses or mid-sentence cutoffs.

This tool applies the 0.75 character-to-token ratio used by GPT-4's cl100k_base tokenizer (±5% accuracy for English text). It's faster than server-side tokenization and works offline. The visual progress bar uses 70% as the warning threshold based on best practices from Anthropic's prompt engineering guide, which recommends keeping prompts under 70% of the context limit to leave headroom for output and prevent token budget surprises. Common model limits: GPT-3.5 (8K/16K), GPT-4 Turbo (32K/128K), Claude 3 (200K), Gemini 1.5 Pro (1M).