Chatbot workload
1,000 requests with 2,000 input tokens and 500 answer tokens.
How this AI API pricing comparison: provider detail works
An AI pricing comparison tool helps you compare the cost side of OpenAI, Claude, and Gemini models. Model choice is not only about benchmark scores. For a SaaS product, the best default model is often the one that delivers acceptable quality at a sustainable price. A small difference in per-million-token pricing can become meaningful when multiplied by large prompts, long outputs, and daily traffic.
This page shows input pricing, output pricing, and the estimated cost for a sample workload. You can adjust the sample input tokens, output tokens, and request volume to see how the ranking changes. Some models are very cheap for input-heavy tasks, while others become expensive when output length is high. If your product depends on long generated reports, output price deserves special attention.
Cost should not be the only selection criteria. Reliability, latency, context length, model quality, tool support, safety behavior, regional availability, and provider terms can all matter. Still, pricing is a useful filter. Many teams ship with a premium model for complex tasks and a cheaper model for classification, extraction, routing, or background jobs.
Use this comparison as a planning baseline. Provider prices can change, and some invoices include caching, batch discounts, search grounding, audio, images, or enterprise arrangements. The static table used here is intentionally transparent so you can audit and update it when providers publish new rates.