🤖 AI API Token Cost Calculator
Estimate what an AI / LLM API call (or a batch of calls) will cost based on input and output token counts and your provider's per-million-token pricing.
Last Updated: July 10, 2026
Token Usage & Pricing
Estimated Cost
🔤 What Is a "Token," Roughly?
A token is a chunk of text a language model reads or generates — not quite a word, not quite a character. This is general, model-agnostic education; exact tokenization differs by provider and model.
| Amount | Approximate Tokens |
|---|---|
| 1 token | ~4 characters, or ~0.75 words (English) |
| ~100 tokens | ~75 words (a short paragraph) |
| ~1,000 tokens | ~750 words (about 1.5 pages) |
| ~10,000 tokens | ~7,500 words (a short e-book chapter) |
💡 Rates Change Often
AI API pricing changes frequently and varies widely between providers and models — from under $1 per million tokens for smaller/open-source models to $15 or more per million output tokens for top-tier models. Always confirm current pricing on your provider's official pricing page before budgeting.
🧮 How This Calculator Works
Formula
Total Cost = [(Input Tokens ÷ 1,000,000 × Input Price) + (Output Tokens ÷ 1,000,000 × Output Price)] × Number of Calls
Example: 500,000 input tokens and 100,000 output tokens per call, at $3/$15 per million, for 10 calls: (0.5×$3 + 0.1×$15) × 10 = ($1.50 + $1.50) × 10 = $30.00.
Why Input and Output Are Priced Differently
Generating (output) tokens is computationally more expensive than reading (input) tokens, so most providers charge a higher per-token rate for output.
💡 Real-World Examples & Use Cases
Three example workloads at illustrative example rates.
Single chatbot reply
1,000 input tokens, 500 output tokens, $3/$15 per 1M, 1 call.
Result: ~$0.0105 — about 1 cent.
Daily batch job
50,000 input + 10,000 output tokens per request, $3/$15 per 1M, 200 requests/day.
Result: $0.30/request × 200 = $60.00/day.
Cheaper open-weight model
2,000,000 input + 500,000 output tokens (aggregated), $0.50/$1.50 per 1M, 1 call.
Result: $1.00 + $0.75 = $1.75.
⚠️ Common Mistakes & Pro Tips
- Forgetting system prompts and context count as input tokens: Long system instructions, chat history, and retrieved documents all add to your input token bill.
- Assuming input and output are priced the same: Output tokens are usually priced several times higher than input tokens.
- Using stale pricing: AI API prices change often — always check your provider's live pricing page before estimating a budget.
- Not multiplying by call volume: A cheap per-call cost can still add up fast at scale — always project against your expected monthly request volume.
🔍 People Also Ask
How many words is one token?
Roughly 0.75 words in English, or about 4 characters per token — but this varies by language and by the specific model's tokenizer.
Why are output tokens more expensive than input tokens?
Generating new text requires more computation per token than reading existing text, so most providers charge a higher rate for output tokens — often 3–5× the input rate.
How can I reduce my AI API costs?
Trim unnecessary context, cache repeated system prompts where supported, use a smaller/cheaper model for simpler tasks, and cap maximum output length where appropriate.
❓ Frequently Asked Questions
Why is output priced higher than input in most APIs?
Generating new tokens (output) is computationally more expensive per token than processing existing tokens (input), so most providers charge a higher rate — often 3 to 5 times the input price — for output.
Does the number of API calls multiply the whole cost?
Yes. Enter the total token counts for one representative call, and the calculator multiplies the per-call cost by your number of calls/requests to estimate total spend for a batch, a day, or any period you\u2019re modeling.
How can I lower my AI API costs?
Reduce unnecessary context (trim prompts, cache repeated instructions), choose a smaller or cheaper model for simpler tasks, and set a maximum output length where your use case allows it.
Do system prompts and chat history count toward token cost?
Yes — anything sent to the model, including system instructions, prior conversation turns, and retrieved documents, counts as input tokens and is billed accordingly.
Is this calculator tied to one specific AI provider?
No. It uses generic, editable input/output token counts and per-million-token pricing so you can model any provider or model — just plug in that provider\u2019s current published rates.
How accurate is the token estimate for my actual text?
The ~4 characters/~0.75 words per token rule is a rough English-language approximation. Different languages, code, and special formatting can tokenize quite differently — use your provider\u2019s official tokenizer tool for exact counts.
Can I use this to estimate a monthly AI budget?
Yes — estimate your typical tokens per call and expected number of calls in a month, then use this calculator to project your monthly spend. Re-check periodically since usage patterns and provider pricing both change.