What's Token?
In Natural Language Processing (NLP), Token It is the basic unit for the large model processing text. It is not necessarily a word or a character. For example, the word "apple" in English might be one Token, and the complex vocabulary "tokenization" may be cut into multiple Tokens. For Chinese, a Chinese word usually corresponds to a Chinese word. 0.6 to 1.5 Token.
Why is Token counting important?
- Cost control: API calls (e.g. OpenAI, Claude) are charged to Token quantities.
- Context limit: Each model has a context window (e.g. GPT-4o is 128K) limit, which can be lost after the model has passed.
- Response speed: The longer the input usually means longer processing time and delays in reasoning.
How can Token consumption be reduced?
Optimizing Prompt is the most efficient way to reduce costs:
- Streamlining of Directives: Delete the meaningless rhetoric.
- Structured input: Models are more efficient using the Markdown or JSON format.
- Few-shot optimization: Example is typical and refined.
- Select the appropriate model: For simple tasks, using GPT-4o Mini or DeepSeek V3 can save more than 90%.
2025 Reference to pricing of mainstream models (token per million)
| Model Name | Enter price | Output price | Characteristics |
|---|---|---|---|
| GPT-4o | $2.50 | $10.00 | All-power flagships. |
| GPT-4o mini | $0.15 | $0.60 | Very high value for money. |
| Claude 3.5 Sonnet | $3.00 | $15.00 | Programming and Logic First |
| DeepSeek V3 | $0.27 | $1.10 | Light of national production, very low cost. |