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

# 计算 Token 数量（Claude）

> 计算 Claude 消息的 token 数量，用于在发送请求前预估成本

## 简介

计算 Claude 消息的 token 数量，用于在发送请求前预估成本。此端点 **不消耗配额**，仅进行本地计算。

## 认证

Bearer Token，如 `Bearer sk-xxxxxxxxxx`

## 请求参数

<ParamField body="model" type="string" required>
  Claude 模型标识，支持的模型包括：

  * `claude-opus-4-8`
  * `claude-sonnet-5`
  * `claude-haiku-4-5`
  * 其他 Claude 系列模型
</ParamField>

<ParamField body="messages" type="array" required>
  对话消息列表，每个元素包含 `role`（user/assistant）和 `content`。`content` 可以是字符串或媒体内容数组。

  支持的内容类型：

  * 纯文本消息
  * 多模态消息（包含图片）
  * 工具调用结果
</ParamField>

<ParamField body="system" type="string">
  系统提示词（可选），可以是字符串或媒体内容数组。用于设定模型的行为和角色。
</ParamField>

<ParamField body="tools" type="array">
  工具定义列表（可选），用于计算工具调用相关的 token 数量。
</ParamField>

## 响应参数

<ResponseField name="input_tokens" type="integer">
  输入消息的总 token 数量，包括：

  * 所有 messages 的 token 数
  * system prompt 的 token 数
  * tools 定义的 token 数（如果有）
</ResponseField>

## 基础示例

<Tabs>
  <Tab title="简单文本消息">
    ```bash theme={null}
    curl -X POST "https://api.mixroute.ai/v1/messages/count_tokens" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer sk-xxxxxxxxxx" \
      -d '{
        "model": "claude-opus-4-8",
        "messages": [
          {
            "role": "user",
            "content": "Hello, how are you?"
          }
        ]
      }'
    ```
  </Tab>

  <Tab title="带 system prompt">
    ```bash theme={null}
    curl -X POST "https://api.mixroute.ai/v1/messages/count_tokens" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer sk-xxxxxxxxxx" \
      -d '{
        "model": "claude-opus-4-8",
        "system": "You are a helpful AI assistant.",
        "messages": [
          {
            "role": "user",
            "content": "What is artificial intelligence?"
          }
        ]
      }'
    ```
  </Tab>

  <Tab title="多轮对话">
    ```bash theme={null}
    curl -X POST "https://api.mixroute.ai/v1/messages/count_tokens" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer sk-xxxxxxxxxx" \
      -d '{
        "model": "claude-opus-4-8",
        "messages": [
          {
            "role": "user",
            "content": "你好"
          },
          {
            "role": "assistant",
            "content": "你好！有什么我可以帮助你的吗？"
          },
          {
            "role": "user",
            "content": "给我讲讲人工智能的历史"
          }
        ]
      }'
    ```
  </Tab>
</Tabs>

## Python 示例

```python theme={null}
from anthropic import Anthropic

client = Anthropic(
    api_key="sk-xxxxxxxxxx",
    base_url="https://api.mixroute.ai"
)

# 计算 token 数量
response = client.messages.count_tokens(
    model="claude-opus-4-8",
    system="You are a helpful assistant.",
    messages=[
        {"role": "user", "content": "Hello, Claude!"}
    ]
)

print(f"Input tokens: {response.input_tokens}")
```

## 响应示例

```json theme={null}
{
  "input_tokens": 14
}
```

## 高级用例

<Tabs>
  <Tab title="带工具定义的计算">
    ```bash theme={null}
    curl -X POST "https://api.mixroute.ai/v1/messages/count_tokens" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer sk-xxxxxxxxxx" \
      -d '{
        "model": "claude-opus-4-8",
        "messages": [
          {
            "role": "user",
            "content": "What is the weather in San Francisco?"
          }
        ],
        "tools": [
          {
            "name": "get_weather",
            "description": "Get the current weather in a given location",
            "input_schema": {
              "type": "object",
              "properties": {
                "location": {
                  "type": "string",
                  "description": "The city and state, e.g. San Francisco, CA"
                }
              },
              "required": ["location"]
            }
          }
        ]
      }'
    ```
  </Tab>

  <Tab title="多模态内容计算">
    ```bash theme={null}
    curl -X POST "https://api.mixroute.ai/v1/messages/count_tokens" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer sk-xxxxxxxxxx" \
      -d '{
        "model": "claude-opus-4-8",
        "messages": [
          {
            "role": "user",
            "content": [
              {
                "type": "text",
                "text": "What is in this image?"
              },
              {
                "type": "image",
                "source": {
                  "type": "url",
                  "url": "https://example.com/image.jpg"
                }
              }
            ]
          }
        ]
      }'
    ```
  </Tab>
</Tabs>

## 使用场景

### 1. 成本预估

在发送大量请求前，先计算 token 数量以预估成本：

```python theme={null}
# 批量计算成本
messages_batch = [...]  # 批量消息
total_tokens = 0

for messages in messages_batch:
    response = client.messages.count_tokens(
        model="claude-opus-4-8",
        messages=messages
    )
    total_tokens += response.input_tokens

# 根据定价计算总成本
cost = total_tokens * price_per_token
print(f"预估成本: ${cost:.4f}")
```

### 2. 上下文窗口管理

检查消息是否超过模型的上下文窗口限制：

```python theme={null}
MAX_CONTEXT_WINDOW = 1000000  # Claude Sonnet 5 的上下文窗口

response = client.messages.count_tokens(
    model="claude-opus-4-8",
    messages=long_conversation
)

if response.input_tokens > MAX_CONTEXT_WINDOW:
    print(f"警告：消息 token 数 ({response.input_tokens}) 超过上下文窗口限制")
    # 执行消息截断或摘要
```

### 3. 优化提示词

比较不同提示词的 token 消耗：

```python theme={null}
prompts = [
    "简洁版提示词...",
    "详细版提示词...",
    "超详细版提示词..."
]

for prompt in prompts:
    response = client.messages.count_tokens(
        model="claude-opus-4-8",
        system=prompt,
        messages=[{"role": "user", "content": "测试"}]
    )
    print(f"{len(prompt)} 字符 -> {response.input_tokens} tokens")
```

## 注意事项

* 此端点不会发起实际的 AI 请求，不消耗配额
* 不包括 `max_tokens` 等输出相关参数，仅计算输入 token 数
* 图片 token 使用固定估算值（约 1000 tokens），实际可能因分辨率不同而变化

## 错误处理

### 缺少必需参数

```json theme={null}
{
  "type": "error",
  "error": {
    "type": "invalid_request_error",
    "message": "Key: 'ClaudeCountTokensRequest.Model' Error:Field validation for 'Model' failed on the 'required' tag"
  }
}
```

### 无效的 API Key

```json theme={null}
{
  "error": {
    "message": "无效的 token",
    "type": "invalid_request_error"
  }
}
```

## 相关资源

* 定价说明 - 了解 token 计费标准
* [模型列表](https://console.mixroute.ai/models) - 查看支持的 Claude 模型
* [创建消息请求（Claude）](/cn/api-reference/endpoint/messages) - 发送实际的 Claude 请求

<RequestExample>
  ```bash cURL theme={null}
  curl --request POST \
    --url https://api.mixroute.ai/v1/messages/count_tokens \
    --header 'Authorization: Bearer sk-xxxxxxxxxx' \
    --header 'Content-Type: application/json' \
    --data '{
      "model": "claude-opus-4-8",
      "messages": [
        {"role": "user", "content": "Hello, how are you?"}
      ]
    }'
  ```

  ```python Python theme={null}
  from anthropic import Anthropic

  client = Anthropic(
      api_key="sk-xxxxxxxxxx",
      base_url="https://api.mixroute.ai"
  )

  response = client.messages.count_tokens(
      model="claude-opus-4-8",
      messages=[
          {"role": "user", "content": "Hello, how are you?"}
      ]
  )
  print(f"Input tokens: {response.input_tokens}")
  ```

  ```javascript JavaScript theme={null}
  const response = await fetch('https://api.mixroute.ai/v1/messages/count_tokens', {
    method: 'POST',
    headers: {
      'Authorization': 'Bearer sk-xxxxxxxxxx',
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      model: 'claude-opus-4-8',
      messages: [
        { role: 'user', content: 'Hello, how are you?' }
      ]
    })
  });
  const data = await response.json();
  console.log(data);
  ```

  ```php PHP theme={null}
  <?php
  $client = new GuzzleHttp\Client();
  $response = $client->post('https://api.mixroute.ai/v1/messages/count_tokens', [
      'headers' => [
          'Authorization' => 'Bearer sk-xxxxxxxxxx',
          'Content-Type' => 'application/json',
      ],
      'json' => [
          'model' => 'claude-opus-4-8',
          'messages' => [
              ['role' => 'user', 'content' => 'Hello, how are you?']
          ]
      ]
  ]);
  echo $response->getBody();
  ```

  ```go Go theme={null}
  package main

  import (
      "bytes"
      "encoding/json"
      "net/http"
  )

  func main() {
      payload := map[string]interface{}{
          "model": "claude-opus-4-8",
          "messages": []map[string]string{
              {"role": "user", "content": "Hello, how are you?"},
          },
      }
      body, _ := json.Marshal(payload)
      req, _ := http.NewRequest("POST", "https://api.mixroute.ai/v1/messages/count_tokens", bytes.NewBuffer(body))
      req.Header.Set("Authorization", "Bearer sk-xxxxxxxxxx")
      req.Header.Set("Content-Type", "application/json")
      http.DefaultClient.Do(req)
  }
  ```

  ```java Java theme={null}
  import java.net.http.*;
  import java.net.URI;

  HttpClient client = HttpClient.newHttpClient();
  String json = """
      {
          "model": "claude-opus-4-8",
          "messages": [{"role": "user", "content": "Hello, how are you?"}]
      }
      """;
  HttpRequest request = HttpRequest.newBuilder()
      .uri(URI.create("https://api.mixroute.ai/v1/messages/count_tokens"))
      .header("Authorization", "Bearer sk-xxxxxxxxxx")
      .header("Content-Type", "application/json")
      .POST(HttpRequest.BodyPublishers.ofString(json))
      .build();
  HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
  System.out.println(response.body());
  ```

  ```ruby Ruby theme={null}
  require 'net/http'
  require 'json'

  uri = URI('https://api.mixroute.ai/v1/messages/count_tokens')
  http = Net::HTTP.new(uri.host, uri.port)
  http.use_ssl = true

  request = Net::HTTP::Post.new(uri)
  request['Authorization'] = 'Bearer sk-xxxxxxxxxx'
  request['Content-Type'] = 'application/json'
  request.body = {
    model: 'claude-opus-4-8',
    messages: [{ role: 'user', content: 'Hello, how are you?' }]
  }.to_json

  response = http.request(request)
  puts response.body
  ```
</RequestExample>

<ResponseExample>
  ```json Response theme={null}
  {
    "input_tokens": 14
  }
  ```
</ResponseExample>