Calculate AI API Costs in Seconds

AI API costs in 2026 range from $0.05 to $150.00 per million input tokens — a 3000x price range. The cost depends on three main factors: which provider you choose (OpenAI, Anthropic, Google, etc.), which model tier you select (efficient vs flagship), and your usage pattern (input-heavy vs output-heavy workloads).

For a typical chatbot processing 10,000 conversations per day with ~1,000 tokens per exchange, monthly costs range from about $15/month using efficient models like GPT-5 nano to $1,500+/month with frontier models like o1 Pro. Most production applications find a sweet spot in the $100–$500/month range using balanced-tier models.

Prices are dropping fast. Since 2023, per-token costs for equivalent capability have fallen roughly 10x. GPT-4 launched at $30/1M input tokens; today, models with comparable performance start at under $1/1M. This trend is driven by hardware improvements, model distillation, and increased competition — with 8 major providers now offering API access.

Output tokens cost more than input tokens — typically 2x to 6x more. This means generation-heavy workloads (content writing, code generation, summarization) are significantly more expensive per-token than retrieval or classification tasks. If you're building a content generation pipeline, optimizing output length and choosing models with favorable output pricing will have the biggest impact on your bill.

Batch processing saves 50%. Most providers now offer batch APIs that process requests asynchronously at half the cost of real-time inference. If your workload doesn't need instant responses — data processing, content generation, analysis pipelines — batch pricing can cut your costs in half without any quality tradeoff. Check our batch pricing page for current rates.

AI API pricing varies dramatically between providers and models. A single request to a frontier model like GPT-5 or Claude Opus can cost 10–100x more than a smaller model like GPT-4o mini or Gemini Flash — yet for many tasks, the cheaper model performs just as well. Choosing the wrong model can mean spending thousands of dollars per month unnecessarily.

AI Cost Check helps developers and teams estimate their actual API spend before committing to a provider. Enter your expected token usage, compare models side by side, and project costs daily, monthly, and yearly. Whether you're building a chatbot, RAG pipeline, code assistant, or content generation tool, understanding your cost structure upfront prevents budget surprises.

All pricing data is sourced directly from provider documentation and updated regularly. We track 8 providers and 74+ models including OpenAI GPT-5, Anthropic Claude, Google Gemini, Mistral, DeepSeek, Meta Llama, xAI Grok, and Cohere — covering both input and output token rates, with batch pricing where available.