AI Token cost calculator
Quickly estimate the API usage costs of mainstream AI models such as OpenAI GPT-5, Claude Opus/Sonnet/Haiku, DeepSeek, and Gemini. Supports single, daily, monthly, and annual cost calculations, with built-in model comparison and cost optimization suggestions.
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Click the context to automatically bring in the suggested Token and number of calls.
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Common usage scenario cost reference
| usage context | Input Token | Output Token | Recommended model | monthly cost estimate |
|---|---|---|---|---|
| chatbot | 2,000 | 500 | Claude Haiku | -- |
| RAG search Q&A | 4,000 | 300 | GPT-5 Mini | -- |
| Customer service system | 1,500 | 300 | DeepSeek Chat | -- |
| Code Agent | 3,000 | 2,000 | Claude Sonnet | -- |
| Translate | 1,000 | 1,000 | Gemini Flash | -- |
| Summary | 5,000 | 500 | GPT-5 Nano | -- |
| AI Coding Assistance | 4,000 | 3,000 | Claude Opus | -- |
A Complete Guide to AI Tokens and API Costs
Learn more about Token, API billing methods and how to reduce costs
What is a Token?
Token is the basic unit for large language models (LLM) to process text. When the model reads or generates text, it does not use "character" or "word" as the unit, but divides the text into individual Tokens. A token can be a complete word, a part of a word (such as a subword), or even a single character.
In English, 1 Token is equal to approximately 0.75 words; in Chinese, due to the particularity of Chinese characters, 1 Token is approximately equal to 1~2 Chinese characters. For example: "Hello, how are you?" is about 5 Tokens, and "The weather is really nice today" is about 6~8 Tokens.
API billing for all AI models is based on the number of tokens, so understanding the basic concept of tokens is crucial to controlling API usage costs.
The difference between Input Token and Output Token
The billing of AI API divides Token into two categories with different prices:
- Input Token: Content provided by the user to the model, including prompts, system commands, dialogue history, etc. The price of Input Token is usually lower because the model only needs to "read" the text.
- Output Token: The answer content generated by the model. The price of Output Token is usually higher because the model requires more computing resources to "generate" the text.
Taking OpenAI GPT-5 as an example, the Input price is $10/M tokens, the Output price is $40/M tokens, and the cost of Output is 4 times that of Input. Therefore, to reduce API costs, reducing the number of Output Tokens is often more effective than reducing Input Tokens.
How is the API billed?
Billing for AI APIs typically follows the following formula:
The price is in "per million Token" (per 1M tokens). For example, if the Input price is $10/M and 1,000 Input Tokens are used, the Input cost is $10 × 1,000 ÷ 1,000,000 = $0.01.
The pricing units and methods of each API provider are slightly different, but the basic principles are the same:Total cost = Input cost + Output cost. Most providers also offer tier discounts (the higher the usage, the lower the unit price) and Batch API deals (50% off for non-instant processing).
How to reduce API costs?
Here are proven AI API cost optimization strategies:
- Choose the right model: Not all tasks require top models. Simple customer service or classification tasks can use GPT-5 Nano or Gemini Flash at 1/30 the cost of flagship models.
- Optimize prompt word length: Simplify system prompt words, remove unnecessary conversation history, and use shorter commands. Shorter Input = lower cost.
- Limit output length: Setting
max_tokensParameter limits the generated length. The cost of Output is usually 3~5 times that of Input, and controlling output is the most meaningful. - Use caching: Both OpenAI and Claude provide Prompt Caching function, and you can enjoy 50~90% discount for repeated system prompt words.
- Using the Batch API: Tasks with non-immediate needs (such as offline data processing) can get 50% off using the Batch API.
- merge request: Merge multiple small requests into one large request to reduce the overhead of repeated system prompt words.
- Review usage regularly: Check API usage statistics every month to identify abnormally high consumption scenarios for optimization.
GPT, Claude, Gemini, DeepSeek cost comparison
The following is the latest API price comparison of major AI models (per million Tokens, unit: USD):
| Platform | model | Input ($/1M) | Output ($/1M) |
|---|---|---|---|
| OpenAI | GPT-5 | $10.00 | $40.00 |
| OpenAI | GPT-5 Mini | $1.25 | $5.00 |
| OpenAI | GPT-5 Nano | $0.35 | $1.40 |
| Claude | Claude Opus | $15.00 | $75.00 |
| Claude | Claude Sonnet | $3.00 | $15.00 |
| Claude | Claude Haiku | $0.25 | $1.25 |
| DeepSeek | DeepSeek Chat | $0.14 | $0.28 |
| DeepSeek | DeepSeek Reasoner | $0.55 | $2.19 |
| Gemini | Gemini 2.5 Pro | $1.25 | $10.00 |
| Gemini | Gemini 2.5 Flash | $0.10 | $0.40 |
AI Token Cost FAQ
Q1: What is the relationship between Token and word count? How to estimate the number of Tokens?
The number of tokens is not equal to the number of words. In English, 1 Token is approximately equal to 0.75 words (approximately 4 characters); in Chinese, 1 Token is approximately equal to 1~2 Chinese characters. Generally speaking, 1,000 Tokens correspond to approximately 750 English words or 500~800 Chinese characters. Most AI platforms (such as OpenAI, Claude) provide the Tokenizer tool to allow you to accurately calculate the number of Tokens.
Q2: Why is the price of Output Token more expensive than Input?
Because the model requires much more computation when generating Output Token than processing Input Token. The Input stage model only needs to understand and encode existing text (similar to "reading"), while the Output stage model needs to predict and decode tokens one by one (similar to "writing"), and each generation requires complete model reasoning. Therefore, the calculation cost of Output Token is usually 3~5 times that of Input.
Q3: Which AI model is the cheapest?
The cheapest option currently on the market is DeepSeek Chat(Input $0.14/M, Output $0.28/M), followed by Gemini 2.5 Flash(Input $0.10/M, Output $0.40/M). If you need to balance cost performance and quality,Claude Sonnet($3/$15) and GPT-5 Mini($1.25/$5) is a good compromise. Top models like Claude Opus ($15/$75) are the most expensive but perform best on complex inference tasks.
Q4: How much is it normal to spend on AI API per month?
It depends on the usage scenario. Daily use by individual developers (100~500 calls per day, choosing a mid-to-low price model) costs about $20~$100 per month. Approximately $100~$1,000 per month for a small team or project (1,000~5,000 times per day). Enterprise-level applications (tens of thousands of times per day) may cost more than $1,000~$10,000 per month. Use this tool to get an accurate estimate of your expected costs.
Q5: Is there a free quota for AI API?
Most platforms offer free credits or free tiers. OpenAI offers $5 free credit for new accounts (valid for 3 months). Claude's API has a similar free trial amount. Gemini provides free Tier (with rate limit), which is very suitable for development and testing. DeepSeek is one of the cheapest options out there and doesn’t require a large upfront payment to use. It is recommended to use the free quota to test first and confirm that the model meets the needs before putting it into official use.
Q6: What is Token Caching? How much can you save?
Token caching is a cost optimization feature provided by OpenAI and Claude. When your system prompts or conversation history are reused in a short period of time, the provider will automatically cache these repeated Input Tokens and bill them at a discount as low as 50~90%. For applications that frequently use the same knowledge base or system instructions (such as customer service robots, RAG systems), enabling caching can save 30~60% of API costs.