Free AI Cost Calculator for OpenAI, Anthropic, and Vertex AI

The calculator uses publicly available pricing data from each provider and typical configuration assumptions. It provides a strong approximation for planning purposes. Actual costs may differ based on your negotiated discounts, regional pricing, and usage patterns that are harder to predict in advance. For example, reasoning models bill for internal thinking tokens that never appear in the visible response, and agentic workflows can multiply model calls from a single user prompt. Treat the estimate as a planning baseline, not a binding quote.

No. This is an estimation tool designed for quick planning and forecasting. For exact pricing, you’ll need provider-specific quotes and actual usage data.

Yes. The calculator doesn’t require credentials or billing data. All inputs are entered manually, and results aren’t stored unless you choose to submit them. Finout follows enterprise-grade security and compliance standards.

Context caching lets a model reuse part of a previous prompt instead of processing the same tokens again from scratch. That reduces your input token count on repeated calls, which lowers cost. Grounding connects the model to external data sources, such as Google Search, at the time of inference. Providers typically charge an extra fee per grounded query. Enabling either option in the calculator adjusts your estimate to reflect those real pricing differences, giving you a more accurate monthly projection.

A token is a small chunk of text, roughly three to four characters or about three-quarters of a word in English. AI providers charge per token because that is the unit of work the model performs. Every time you send a prompt, the model counts the tokens going in (input) and the tokens it generates back (output). Providers charge different rates for each direction, and output tokens typically cost more. The more tokens your workload uses per request, the higher your monthly bill. That is why the calculator asks for your expected input and output token volumes before projecting a cost.

Input tokens are the prompt you send to the model. Output tokens are the response the model generates. Generating text requires more compute than reading it, which is why providers charge more for output tokens across most models. For example, a model might charge $2.00 per million input tokens and $8.00 per million output tokens. If your workload produces long responses relative to short prompts, output costs will drive most of your bill. The calculator separates input and output volumes for this reason: the ratio between them often matters more than the total token count.

The calculator currently supports OpenAI, Anthropic, and Google Vertex AI. Within each provider, you can select the specific model you plan to use, then enter your expected usage to see a projected monthly cost. If you need to compare workloads across providers, you can add multiple workloads side by side and export the results as JSON or CSV for further analysis.

The calculator gives you a planning baseline. Once your workloads are live, actual spend will shift as usage grows, models change, and your team scales. That is where a platform like Finout picks up. Finout is an enterprise-grade FinOps platform for cloud and AI spend. It consolidates AWS, Azure, GCP, OCI, Kubernetes, SaaS, and AI costs in one unified view, and allocates every dollar to the team, product, or workload that generated it. Billy, Finout's AI FinOps assistant, surfaces anomalies and answers cost questions in plain language before they become budget surprises. If your estimates from this calculator are revealing spend you need to track and govern, Finout is where that work continues.