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

# Usage Accounting

The Anannas API provides *built-in* **Usage Accounting** that allows you to track AI model usage without making additional API calls. This feature provides detailed information about token counts, costs, and caching status directly in your API responses.

### Usage Information

When enabled, the API will return detailed usage information including:

1. Prompt and completion token counts using the model’s native tokenizer
2. Cost in credits
3. Reasoning token counts (if applicable)
4. Cached token counts (if available)

This information is included in the last SSE message for streaming responses, or in the complete response for non-streaming requests.

### Enabling Usage Accounting

You can enable usage accounting in your requests by including the `usage` parameter:

```bash theme={null}
{
  "model": "your-model",
  "messages": [],
  "usage": {
    "include": true
  }
}
```

### Response Format

When usage accounting is enabled, the response will include a `usage` object with detailed token information:

```bash theme={null}
{
  "object": "chat.completion.chunk",
  "usage": {
    "completion_tokens": 2,
    "completion_tokens_details": {
      "reasoning_tokens": 0
    },
    "cost": 0.95,
    "cost_details": {
      "upstream_inference_cost": 19
    },
    "prompt_tokens": 194,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "audio_tokens": 0
    },
    "total_tokens": 196
  }
}
```

`cached_tokens` is the number of tokens that were *read* from the cache. At this point in time, we do not support retrieving the number of tokens that were *written* to the cache.

### Cost Breakdown

The usage response includes detailed cost information:\
`cost`: The total amount charged to your account

<Note>
  Performance Impact

  Enabling usage accounting will add a few hundred milliseconds to the last response as the API calculates token counts and costs. This only affects the final message and does not impact overall streaming performance.
</Note>

### Benefits

1. **Efficiency**: Get usage information without making separate API calls
2. **Accuracy**: Token counts are calculated using the model’s native tokenizer
3. **Transparency**: Track costs and cached token usage in real-time
4. **Detailed Breakdown**: Separate counts for prompt, completion, reasoning, and cached tokens

### Best Practices

1. Enable usage tracking when you need to monitor token consumption or costs
2. Account for the slight delay in the final response when usage accounting is enabled
3. Consider implementing usage tracking in development to optimize token usage before production
4. Use the cached token information to optimize your application’s performance

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