AI API Cost Calculator — GPT, Claude & Gemini Token Pricing
Estimate and compare OpenAI, Anthropic, and Gemini API costs before you build.
100% in your browser — files never uploaded
How AI API Pricing Works
Providers like OpenAI, Anthropic, and Google bill per token — roughly 4 characters or ¾ of an English word. Input (prompt) tokens and output (response) tokens are priced separately, with output typically costing 3–5× more. Your monthly bill is: (input tokens × input rate + output tokens × output rate), summed across all requests.
Estimating Tokens From Text
Paste any text into the counter to see its approximate token count using the standard chars÷4 heuristic. For budgeting, estimate your average prompt size, average response size, and monthly request volume — the calculator multiplies these against current per-model rates to project spend.
Choosing a Model by Cost
The comparison chart puts 13 models side by side at your exact usage. Smaller models often cost 10–60× less than flagships; if your task is classification, extraction, or simple chat, a compact model usually delivers equivalent results at a fraction of the price. Reserve flagship models for reasoning-heavy work.
Keeping API Bills Under Control
Cap max output tokens per request, cache repeated prompts, batch where providers offer discounts, and monitor with usage alerts. Pricing changes frequently — the rates here carry a lastVerified date, and you should re-check before committing to a production budget.
Input and Output Tokens Are Priced Differently — Why That Matters
Nearly every provider charges more for output tokens than input tokens, typically 3–5x, because generating text costs more compute than reading it. This flips how you should think about cost: a chat feature with short prompts and long responses will bill mostly on the output side, while a summarization or classification tool with long input and a short answer bills mostly on input. Knowing which side of your workload dominates tells you which lever — trimming prompt length or capping response length — actually moves your bill.
Why the Chars-Divided-By-4 Token Estimate Isn't Exact
The roughly-4-characters-per-token heuristic used for quick estimates is an English-text average, not an exact count — actual tokenization depends on the model's specific tokenizer, and code, non-English text, and unusual punctuation all tokenize differently than prose. For a rough monthly budget projection this approximation is good enough, which is exactly what this calculator uses it for; for billing-critical precision on a specific request, a provider's own tokenizer will always be the authoritative count.
Right-Sizing the Model Instead of Defaulting to the Flagship
It's common to default every API call to the most capable model available, but flagship models often cost 10–60x more than smaller models in the same family for tasks that don't need frontier reasoning — classification, extraction, short chat replies, and simple formatting rarely benefit from the largest model. This calculator's side-by-side comparison across 13 models at your actual usage volume makes that gap visible in rupee or dollar terms rather than as an abstract pricing table, which is usually what turns a compact-model swap from a suggestion into a decision.
Frequently asked questions
How is AI API cost calculated?
APIs bill per token, split between input and output. Cost per request = (input tokens ÷ 1M × input price) + (output tokens ÷ 1M × output price). Multiply by monthly requests for total spend. Output rates run 4–6x input rates on most models, so response length dominates the bill.
How many tokens is my text?
Roughly 1 token per 4 characters of English, or about 750 words per 1,000 tokens. Use the paste-text mode in this calculator to count a real prompt — the estimate runs locally in your browser and nothing is uploaded.
Which AI API is cheapest in 2026?
DeepSeek V3.2 ($0.28/$0.42 per million tokens) and GPT-5.4 nano ($0.20/$1.25) are the cheapest current models for high-volume simple tasks. Among frontier models, Gemini 3.1 Pro ($2/$12) undercuts Claude Sonnet 4.6 ($3/$15) and GPT-5.5 ($5/$30) on list price.
Why is my real bill higher than the estimate?
Reasoning models bill hidden internal thinking tokens as output, retries re-send full input, and conversation history compounds input size every turn. This calculator uses base list rates; treat it as a floor and add margin for reasoning-heavy or agentic workloads.
How can I reduce my AI API costs?
Three levers: route simple tasks to cheaper model tiers instead of defaulting to the flagship, use prompt caching for repeated system prompts (up to 90% off cached input), and send non-urgent work through batch APIs for a 50% discount on most providers.