OpenAI API Cost Calculator
Estimate your OpenAI API costs for GPT-4o, GPT-4, GPT-3.5, and more.
What is the OpenAI API Cost Calculator?
The OpenAI API Cost Calculator helps developers, startups, and businesses estimate the cost of using OpenAI's language models in their applications. Whether you're building a chatbot, content generation tool, code assistant, or any AI-powered product — understanding your API costs before you scale is critical for building a sustainable business.
OpenAI's pricing is based on tokens — the fundamental units of text that language models process. Each model has different pricing for input tokens (what you send to the API) and output tokens (what the model generates). Prices vary dramatically between models: GPT-3.5-turbo is roughly 60x cheaper than GPT-4 for input tokens, making model selection a crucial cost optimization lever.
This calculator supports all major OpenAI models including GPT-4o (the latest flagship model), GPT-4o-mini (cost-optimized), GPT-4-turbo, GPT-4, GPT-3.5-turbo, and o1 (reasoning model). Simply select your model, enter your average token counts per request, and specify your daily request volume to get instant cost projections.
Understanding token costs is essential for product planning. A typical chatbot message might use 500 input tokens and 200 output tokens. A code generation request might use 1,000 input tokens and 500 output tokens. A document summarization task might use 4,000 input tokens and 500 output tokens. The cost difference between these use cases can be dramatic at scale.
For teams building production AI systems, this calculator helps you model different scenarios: What happens to your costs if you double your user base? What's the cost difference between GPT-4o and GPT-4o-mini for your use case? How much would you save by reducing your average prompt length by 20%? These are the questions that determine whether your AI product is economically viable.
All calculations use OpenAI's published pricing as of 2024. Prices may change — always check OpenAI's official pricing page for the most current rates.
How Does the OpenAI API Cost Calculator Work?
The OpenAI API Cost Calculator works in three simple steps:
1. Select your model — Choose from GPT-4o, GPT-4o-mini, GPT-4-turbo, GPT-4, GPT-3.5-turbo, or o1. Each has different pricing per million tokens.
2. Enter token counts — Specify your average input tokens (prompt length) and output tokens (response length) per request. A rough guide: 1 token ≈ 4 characters or ¾ of a word in English.
3. Set daily request volume — How many API requests does your application make per day?
The calculator multiplies your token usage by the model-specific per-token pricing, then scales to daily and monthly costs. Input and output tokens are priced differently — output tokens are typically 2-4x more expensive because they require more computation.
Formula & Calculation Method
Cost Per Request:
Cost/Request = (Input Tokens / 1,000,000 × Input Price) + (Output Tokens / 1,000,000 × Output Price)
Daily Cost:
Daily Cost = Cost Per Request × Requests Per Day
Monthly Cost:
Monthly Cost = Daily Cost × 30
Model Pricing (per million tokens):
| Model | Input | Output |
|-------|-------|--------|
| GPT-4o | $2.50 | $10.00 |
| GPT-4o-mini | $0.15 | $0.60 |
| GPT-4-turbo | $10.00 | $30.00 |
| GPT-4 | $30.00 | $60.00 |
| GPT-3.5-turbo | $0.50 | $1.50 |
| o1 | $15.00 | $60.00 |
Note: Prices are per million tokens. Divide by 1,000,000 to get per-token cost.
Example Calculation
Example: Chatbot using GPT-4o with 1,000 daily requests
- Model: GPT-4o
- Input tokens per request: 500 (typical user message + system prompt)
- Output tokens per request: 300 (typical assistant response)
- Requests per day: 1,000
Cost per request:
- Input cost: (500 / 1,000,000) × $2.50 = $0.00125
- Output cost: (300 / 1,000,000) × $10.00 = $0.003
- Total per request: $0.00425
Daily cost: $0.00425 × 1,000 = $4.25/day
Monthly cost: $4.25 × 30 = $127.50/month
For comparison, the same usage with GPT-4o-mini would cost only $7.65/month — a 94% savings! This shows why model selection is such an important optimization lever.