> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agipower.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Usage

# Usage Analytics

AGIPower provides comprehensive usage analytics capabilities to help you monitor and analyze API calls, service provider performance, and model efficiency in real-time. Through usage analytics, you can gain deep insights into key metrics such as token consumption, API request volume, and response times, enabling you to optimize application performance and control costs.

> **Note**: The data displayed on this page excludes usage from subscription plans and only tracks Pay As You Go usage.

## Usage Overview

In the "Usage" tab, you can view overall resource consumption, including token usage and API request counts.

![usage](https://cdn.marmot-cloud.com/storage/agipower/2026/01/19/VKnjOtl/yongliangfenxi-gailan.png)

Filter Options:

* **Time Range**: Filter data by granularity such as "Month", "Week", or "Day".
* **API Keys**: Filter data by specific API keys, supporting "All Keys" or individual keys.
* **Model Scope**: Select "All Models" or specify particular model types for analysis.

### Metric Descriptions

| Metric                 | Description                                                 |
| ---------------------- | ----------------------------------------------------------- |
| **Total Token Usage**  | Total token usage across all models (input + output).       |
| **Input Token Usage**  | Total number of input tokens across all requests.           |
| **Output Token Usage** | Total number of output tokens across all responses.         |
| **Total API Requests** | Total number of API calls within the specified time period. |

### Analysis by Dimension

* **Usage by Model**\
  Displays token usage distribution across different models in charts or tables, helping identify high-consumption models.

![usage](https://cdn.marmot-cloud.com/storage/agipower/2026/01/19/RaM5XU5/yongliangfenxi-Usage-by-Model.png)

* **Usage by Token Type**\
  Separately tracks input and output token usage, making it easier to evaluate the cost structure of requests and responses.

![usage](https://cdn.marmot-cloud.com/storage/agipower/2026/01/19/F1SB1uu/yongliangfenxi-Usage-by-Token-Type.png)

* **Usage by API Key**\
  Shows token and request usage across different API keys, suitable for usage isolation and auditing in multi-user or multi-project scenarios.

![usage](https://cdn.marmot-cloud.com/storage/agipower/2026/01/19/vCxvX0T/yongliangfenxi-Usage-by-API-Key.png)

* **Web Search Usage**\
  Displays token consumption and call counts for requests with web search enabled (if applicable), helping assess the frequency and cost of enhanced retrieval features.

![usage](https://cdn.marmot-cloud.com/storage/agipower/2026/01/19/sFwA29Z/yongliangfenxi-Web-Search-Usage.png)

## Provider

Switch to the "Provider" tab to view the performance of different AI service providers.

![usage](https://cdn.marmot-cloud.com/storage/agipower/2026/01/19/Pbg1WCN/yongliangfenxi-Provider.png)

### Metric Descriptions

| Metric                        | Description                                                                           |
| ----------------------------- | ------------------------------------------------------------------------------------- |
| **Primary Provider**          | The primary AI service provider currently in use (e.g., Google Gemini, OpenAI, etc.). |
| **Provider Count**            | Total number of service providers used.                                               |
| **Average Success Rate**      | Average success rate across all requests, reflecting service reliability.             |
| **Fastest Response Provider** | The service provider with the shortest response time.                                 |

### Analysis by Dimension

* **Token Distribution**\
  Shows token usage distribution across providers, making it easier to evaluate resource allocation efficiency.

![usage](https://cdn.marmot-cloud.com/storage/agipower/2026/01/19/hz0tFzY/yongliangfenxi-Provider-Token-Distribution.png)

* **Request Distribution**\
  Displays API request count distribution by service provider, reflecting the call load for each provider.

![usage](https://cdn.marmot-cloud.com/storage/agipower/2026/01/19/DyqPfmR/yongliangfenxi-Provider-Request-Distribution.png)

> **Tip**: Combine model and provider filters to perform in-depth analysis of specific combinations' performance.

## Performance

In the "Performance" tab, you can view performance metrics for API calls to evaluate model response efficiency and service quality.

![usage](https://cdn.marmot-cloud.com/storage/agipower/2026/01/19/9Y5ytNg/yongliangfenxi-Performance-gailan.png)

### Metric Descriptions

| Metric                          | Description                                                                                      |
| ------------------------------- | ------------------------------------------------------------------------------------------------ |
| **Average Latency**             | Average response latency in milliseconds; lower values indicate faster responses.                |
| **Average Throughput**          | Average throughput in tokens per second, reflecting processing capacity per unit time.           |
| **Fastest / Slowest**           | Lists the fastest and slowest model response records, helping identify performance bottlenecks.  |
| **Highest / Lowest Throughput** | Shows models with the highest and lowest throughput, assisting with load balancing optimization. |

### Analysis by Model

* **First Token Latency by Model**\
  Displays the latency for generating the first token across different models.
  > **Note**: First token latency is a critical user experience metric; lower values indicate more responsive performance.
  * Displays latency distribution across models in charts or lists.
  * Supports filtering by model to quickly identify high-latency models.

* **Throughput by Model**\
  Displays throughput (tokens per second) across different models.
  > **Note**: The higher the value, the better the performance.
  * Used for comparing processing efficiency across models within a given timeframe.
  * Helps select high-throughput models to improve overall system responsiveness.

***

<Tip title="Contact Us">
  If you encounter any issues or have suggestions and feedback, feel free to reach out to us:

  * **Official Website**: [https://agipower.ai](https://agipower.ai)
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  For more contact information and details, please visit our [Contact Us page](/en/help/contact).
</Tip>
