Figuring out how much an AI API call will cost before you commit to a model is surprisingly tricky. Token counts aren’t obvious, pricing tables vary wildly between providers, and small changes in prompt length or output ratio can swing your monthly bill by hundreds of dollars. This free AI token and cost estimator does the math for you — instantly, in your browser, with no sign-up required.

Paste any text, choose your output ratio and call volume, and see a live cost breakdown across 10+ models from OpenAI, Anthropic, and Google. It’s the fastest way to compare GPT-4o vs Claude Sonnet vs Gemini Flash before you build.

How to Use the AI Token & Cost Estimator

• Paste your prompt or text into the input box. This is your “input” — the text you send to the model. You can type freely or use one of the quick presets (Short prompt, Typical prompt, Long document) to load a realistic example.
• Set the output ratio. Most API calls generate a response longer or shorter than the input. A ratio of 1× means the output is roughly the same length as your input. Use 0.5× for short answers, 2–4× for detailed responses, and 8× for long-form generation like articles or reports.
• Enter your call volume. Running 1 test call costs almost nothing — but at 10K or 100K calls per month, the numbers get real. Select the volume that matches your expected usage.
• Review the model comparison table. Every model is shown with its per-million-token rate, a relative cost bar, and a total cost for your specific input/output/volume combination. Click any model to select it and see its cost highlighted at the top.
• Copy your summary. Hit “Copy cost summary” to get a plain-text breakdown you can paste into a doc, Slack, or a client proposal.

Understanding the Results

The estimator uses a BPE (Byte Pair Encoding) approximation — roughly 4 characters per token for standard English prose, adjusted upward for code-heavy content which tends to tokenise more efficiently. Real token counts from the API may vary by 5–15%, so treat this as a planning tool rather than an invoice preview.

💡 Tip: For production cost planning, run your actual prompt through the model’s tokenizer (available free via the OpenAI Playground or Anthropic Console) and use those numbers for final budgeting.

Frequently Asked Questions

What’s the difference between input tokens and output tokens?

Input tokens are the text you send to the model — your prompt, instructions, and any context. Output tokens are the text the model generates in response. Most providers charge different rates for each, and output tokens are usually 3–5× more expensive.

Which AI model is cheapest for high-volume use?

For high-volume, cost-sensitive workloads, Gemini 2.0 Flash and Claude Haiku 4.5 consistently come in cheapest. GPT-4o mini is also a strong option. The right choice depends on your quality threshold — use this tool to see the cost gap against more capable models like GPT-4o or Claude Sonnet.

Does this tool send my text to any server?

No. All processing happens entirely in your browser using JavaScript. Nothing you type is transmitted, stored, or logged anywhere.

How accurate are the token estimates?

The estimator uses a character-based BPE approximation. For standard English text it’s typically within 10% of the actual token count. Code, non-Latin languages, and heavily formatted text may be less accurate. For precise counts, use the provider’s official tokenizer.

Are the prices up to date?

Prices reflect published per-million-token rates as of Q1 2026. AI model pricing changes frequently — always verify at each provider’s current pricing page before making financial decisions.