Updated AI Pricing & Token Tool

AI API Cost Calculator

Estimate AI API costs for OpenAI, Anthropic, Gemini and custom models. Enter input and output tokens, number of requests or dataset size to see per-request cost, project cost and normalized pricing per 1K and 1M tokens.

OpenAI · Anthropic · Gemini Custom Providers Tokens & Requests Budget Planning

Calculate AI API Token Costs

Use this AI API Cost Calculator to estimate the price of language model calls across major providers. Select a model family such as OpenAI GPT-5, Anthropic Claude or Google Gemini, or define your own custom pricing, then plug in token counts and request volumes to understand your likely spend.

The calculator focuses on text token pricing for input and output tokens. It does not include storage, vector database fees, or additional charges for tools, images or video unless you bake those into your custom token price.

Used to project daily and monthly cost from per-request cost.

This tab is ideal when you know a typical request pattern (for example, 2K input tokens and 500 output tokens) and want to understand the cost per request and at scale over days or months.

Use this tab when you already have aggregated token usage from logs or a token counter. Enter total input and output tokens for the whole project or time period you care.

Default 256 tokens/KB (≈4 characters per token). Adjust based on your data.
For short answers, values like 200–400 are common; for long outputs, use larger numbers.

This tab is useful when you only know the approximate corpus size. The calculator converts size to an input token estimate, then scales output tokens based on a configurable output-to-input ratio.

The comparison tab uses the same per-request token pattern for all predefined models and ranks them by total cost per request. This gives a quick sense of which model families are cheaper or more expensive for your usage profile.

AI API Cost Calculator – Plan Your Token Budget Across Providers

Large language models (LLMs) are usually billed by tokens rather than by request. As your usage grows across chatbots, RAG systems, agents and background automations, it becomes important to predict and compare costs across providers. The AI API Cost Calculator from MyTimeCalculator helps you translate tokens, requests and dataset sizes into clear price estimates.

With support for OpenAI, Anthropic Claude, Google Gemini and custom providers, you can model per-request costs, aggregate project spending and rough budgets for new data pipelines in one place. The calculator also normalizes prices to per-1K and per-1M token equivalents so you can compare model families fairly.

1. OpenAI, Anthropic, Gemini and Custom Models in One View

Different vendors publish pricing in slightly different formats, but the underlying idea is the same: a price per input token and a price per output token. The calculator brings these together into a unified token model:

  • OpenAI: GPT-5.1, GPT-5 mini and GPT-5 nano style models with distinct input and output token rates.
  • Anthropic Claude: Haiku, Sonnet and Opus tiers with varying cost and capability trade-offs.
  • Google Gemini: Flash/Flash-Lite and Pro tiers for cost-sensitive vs. more capable workloads.
  • Custom provider: Any model where you can specify an input and output price per 1K or 1M tokens.

Under the hood, all of these options are converted to a single unit: cost per 1M tokens for input and output. That makes it easy to mix “official” prices with your own negotiated or internal costs.

2. Three Ways to Estimate AI API Costs

The calculator offers three main workflows depending on which information you currently have:

  • Per-request cost: Enter input and output tokens for a typical request, plus optional request volume. This is ideal when you are prototyping a new feature and want to know the cost per call and per day.
  • Project token cost: Enter total input and output tokens from logs or a token counter. This gives you the exact cost over a fixed period or for a completed job.
  • Dataset-based estimation: Start from dataset size in KB/MB/GB and an assumed tokens-per-KB density, then specify an average output-to-input ratio. This is helpful when you only know corpus size.

3. How to Use the AI API Cost Calculator

  1. Select a provider. Choose OpenAI, Anthropic, Gemini or “Custom provider / model” from the Provider dropdown.
  2. Pick a model or define custom pricing. For the built-in providers, select a model tier. For a custom provider, enter a descriptive name and set input/output prices per 1K or 1M tokens.
  3. Choose the tab that matches your data: Per-Request Cost, Project Token Cost or Dataset → Tokens → Cost.
  4. Enter your token or size numbers. For per-request, use a typical input/output token pattern. For project cost, enter total tokens. For dataset-based, supply size and density assumptions.
  5. Run the calculation. Click theevant calculate button to see total cost, per-request cost, and normalized per-1K and per-1M token prices.
  6. Compare models. Use the Model Comparison tab to see how different predefined models rank on cost for the same token pattern.

4. When to Use Per-Request vs Project-Level Estimates

Per-request estimates are especially useful in product design: they show how much each user action or agent step might cost. Project-level estimates, by contrast, are better for overall budgeting, contract planning and answering questions like “How much did our assistant cost to run last month?” The calculator lets you move between these views using the same pricing assumptions.

5. Limits and Assumptions

Like any estimator, the AI API Cost Calculator makes a few simplifying assumptions:

  • It focuses on text token pricing and ignores storage, vector databases and network egress.
  • It assumes that input and output tokens are billed at fixed per-1M token rates without special discounts.
  • In dataset mode, it translates corpus size to tokens using a constant density, which may vary by dataset.

In practice, you can refine these assumptions over time by sampling real traffic, measuring token density on representative documents and updating any custom token prices to reflect discounts or caching.

Related Tools from MyTimeCalculator

AI API Cost Calculator FAQs

Frequently Asked Questions

Quick answers to common questions token pricing, dataset-based estimates and comparing AI model costs across providers.

Dataset-based estimates use a tokens-per-KB density plus an average output-to-input ratio, so they are approximate by design. They are most useful for early budgeting when you do not yet have token logs. For tighter accuracy, measure tokens on a small sample of your data with a tokenizer, compute the actual tokens per KB and update the density value in the calculator.

The calculator is designed around text token pricing. Some providers convert images, audio or video into token-equivalent billing units, but the exact details differ. If you know an effective per-token cost for a multimodal model, you can still use the Custom provider mode and treat that number as your blended token price, but the calculator will not model image or video-specific pricing tiers explicitly.

Many vendors offer lower prices for batch processing, cached prompts or enterprise contracts. The simplest way to include these in your estimates is to compute an effective average price per 1K or 1M tokens, then enter that into the Custom provider fields. That way, the calculator still works with normalized token units while reflecting your negotiated or discounted rates.

Input tokens measure the size of your prompt or context window, while output tokens measure the length of the model’s response. Many pricing tables charge different rates for input and output tokens. Long contexts with short answers are dominated by input costs; long generations with small prompts are dominated by output costs. The calculator keeps these components separate so you can see how each side contributes to the total cost.

Yes. The Model Cost Comparison tab runs the same input and output token pattern across a set of predefined models from OpenAI, Anthropic and Gemini. It then ranks them by cost per request so you can quickly see which models are cheaper or more expensive for your specific usage profile. You can adjust the token pattern and rerun the comparison as often as you like.

AI model pricing evolves over time, especially as new tiers and discounts are introduced. It is a good idea toiew your provider’s pricing documentation periodically and update any hard-coded prices or custom token rates in the calculator so they stay in sync with the latest published values and your own contracts.

Related Calculators