Enter token counts, requests per day, and active days per month.
Prices are shown in USD per one million tokens. Select a provider to see its currently supported models.
How AI pricing works
A simple estimate built from your actual workload.
AI providers usually charge separately for input and output tokens. This calculator applies the selected model's published price per million tokens to the usage pattern you enter, then scales the result across your request volume and active days.
Estimates exclude provider-specific discounts, cached-token pricing, taxes, and other charges that may apply to your account. Always confirm final rates with your provider before committing to a production budget.
01
Input tokens
The tokens sent with each request, including prompts and context.
02
Output tokens
The tokens generated by the model in each response.
03
Usage volume
Requests per day and active days turn unit pricing into a budget.
Common Questions
What is an AI pricing calculator?
An AI pricing calculator helps you estimate the cost of using AI models through their APIs. Enter the number of input and output tokens, choose a model, and the calculator estimates how much your request or workload may cost.
How is AI API pricing calculated?
Most AI providers charge based on token usage. Input tokens and output tokens usually have different prices. The total cost is calculated by multiplying the number of tokens used by the model's price per token.
What are input and output tokens?
Input tokens are the tokens sent to the AI model, including your prompt, system instructions, and conversation context. Output tokens are the tokens generated by the model in its response. Providers may charge different rates for input and output tokens.
How many tokens are in 1,000 words?
The exact number depends on the language, formatting, and model tokenizer. As a rough estimate, 1,000 English words often correspond to around 1,300–1,500 tokens. For accurate estimates, use a token calculator with the actual text you plan to send.
Can I compare AI model costs?
Yes. Comparing pricing across models can help you understand how much the same workload may cost with different models. This is useful when evaluating models for chat applications, AI agents, document processing, RAG systems, and other AI-powered products.
Why do different AI models have different prices?
AI models differ in size, capabilities, context windows, reasoning features, speed, and infrastructure requirements. More capable models are often more expensive, while smaller models may provide lower costs and faster responses for simpler tasks.
How can I estimate my monthly AI API cost?
Estimate the average number of input and output tokens used per request, multiply it by the expected number of requests per month, and apply the model's token pricing. The AI Pricing Calculator can help you estimate these costs before deploying an application to production.
Does context length affect AI API cost?
Yes. Conversation history, system prompts, retrieved documents, and other context sent with every request can increase the number of input tokens. Long contexts can therefore significantly increase the cost of an AI application.
Is the cheapest AI model always the best choice?
Not necessarily. Cost is only one part of model selection. You should also evaluate response quality, latency, reliability, context requirements, and how well the model performs on your specific use case. A more expensive model may sometimes require fewer retries or produce better results.
How can I reduce AI API costs?
Common strategies include reducing unnecessary context, shortening prompts, limiting output length, using smaller models for simpler tasks, caching reusable content where supported, and selecting different models for different workloads. The goal is to optimize cost without reducing the quality required by your application.