AI Pricing Index

What Is the Real Cost of AI?

Live pricing data for 20+ AI models and tools — refreshed monthly. No signup required.

Last updated: 2026-05 · Source: OpenRouter

Key Findings 2026-05

• Frontier AI expenses amount to $21.13 per million tokens — this is roughly $0.02 for a 750-word blog post created by GPT-4o or Claude Sonnet. For the majority of small businesses handling under 10,000 tasks monthly, AI API costs remain under $50/month.
• Budget models provide 80-90% of frontier quality at a 28x cost reduction. The Budget Index sits at $0.76/1M tokens — models such as Gemini Flash, DeepSeek V3, and Llama 4 manage email drafting, customer replies, and document processing at near-zero marginal cost.
• The pricing disparity between providers is growing. OpenAI's o-series reasoning models can cost up to $262/1M tokens, whereas open-source alternatives from Meta and DeepSeek deliver robust results under $1/1M tokens. The "right" model choice depends entirely on the specific task.
• Most small businesses are paying too much. Consumer subscriptions ($20-200/month) come with usage caps and features most users don't need. API access to the same models costs 5-20x less for typical small business workloads.

Data sourced from OpenRouter public API. Refreshed monthly. Cite as: AIscending AI Pricing Index, 2026-05. Questions? [email protected]

How to Interpret These Numbers

The AI CPI monitors the average cost of utilizing top-tier AI models (GPT-4o, Claude Sonnet, Gemini Pro, etc.) per million tokens — approximately 750,000 words of input/output combined. If you are building with AI APIs, this serves as your benchmark.

The Budget Index tracks the same metric for cost-efficient models (Gemini Flash, DeepSeek, Llama, Mistral Small). These deliver 80-90% of frontier quality at a fraction of the price — and they represent what most small businesses should actually be using.

Guide to Reading the Data

Blended Price represents the actual cost per million tokens using a typical mix of 75% input and 25% output. Consider it the "real-world cost" of operating the model. Input tokens (what you send) are almost always cheaper than output tokens (what the model writes back), so the blend provides a single number to compare apples to apples.

Per 1M Tokens — one million tokens is approximately 750,000 words, or about 10 novels. That sounds like a massive amount, but most small business tasks use only 1,000 to 5,000 tokens per request. A quick customer email might use 500 tokens. Summarizing a 10-page contract might use 8,000. The per-million pricing is simply how providers quote rates — divide by 1,000 to get the cost of a single typical request.

Context Length determines how much text the model can "see" at once. A model with 128K context can process about 96,000 words in a single request — enough for a full book. Longer context means you can feed it larger documents without splitting them up. Most everyday tasks require less than 8K tokens of context.

AI CPI is our composite index tracking how frontier AI pricing changes month over month — similar to the Consumer Price Index, but for AI. When the AI CPI drops, it means the same quality of AI output is becoming more affordable. We track this to help you time your AI adoption to real market conditions, not hype cycles.

Current AI Model Pricing

Blended price per 1M tokens (75% input, 25% output). Lower indicates cheaper cost.

API Pricing — Per 1M Tokens

What developers and automation builders pay. All prices in USD via OpenRouter.

Tip: click any column header to sort.