free_tool
Prompt Token & Cost Inspector
Paste a prompt and see exactly what it costs before you ship it: an exact token count from a real BPE tokenizer, the price per call and per month across Claude, GPT-4o and Gemini, and how much of each model's context window it eats. It runs in your browser, so the prompt never leaves the page.
Input tokens (estimate)
90
64 words · 357 chars · 18% whitespace
| Model | / call | / month | ctx |
|---|---|---|---|
| Claude Haiku | $0.0021 | $62.16 | <0.1% |
| Claude Sonnet | $0.0078 | $233.10 | <0.1% |
| Claude Opus | $0.04 | $1,165.50 | <0.1% |
| GPT-4o mini | $0.00031 | $9.41 | <0.1% |
| GPT-4o | $0.0052 | $156.75 | <0.1% |
| Gemini 1.5 Flash | $0.00016 | $4.70 | <0.1% |
| Gemini 1.5 Pro | $0.0026 | $78.38 | <0.1% |
Tokenized with o200k (GPT-4o family); other models tokenize within a few percent. List prices per 1M tokens, captured 2026-06. "ctx" = prompt as a share of the model's context window.
Prompt ballooning your bill or blowing the context window? I cut token footprint with caching, retrieval, and tighter prompts without losing quality.
Trim your token bill: book a callTokenized with o200k (the GPT-4o family encoding). Claude and Gemini use their own tokenizers, but for typical English and code the counts land within a few percent, which is close enough to budget and to compare prompts.
why_it_matters
Every token ships on every call
A prompt you write once runs millions of times. A bloated system prompt or an over-stuffed few-shot block isn't a one-time cost; it's a tax on every request, paid in latency and dollars for the life of the feature. Seeing the monthly number next to the token count is usually what makes teams trim.
Context fit matters just as much. A prompt that quietly grows past the window doesn't error politely; it truncates, and the model starts ignoring the instructions you thought were guaranteed. Watch the context column as your retrieved context and history grow.
Token bill climbing faster than usage?
I'll find where the tokens go (bloated prompts, context you can cache, retrieval you can tighten) and cut the bill without losing answer quality. Book a call, or leave your email.