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POST
https://console.mixroute.io
/
v1
/
messages
/
count_tokens
curl --request POST \
  --url https://console.mixroute.io/v1/messages/count_tokens \
  --header 'Authorization: Bearer sk-xxxxxxxxxx' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "claude-sonnet-4-5-20250929",
    "messages": [
      {"role": "user", "content": "Hello, how are you?"}
    ]
  }'
{
  "input_tokens": 14
}

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

model
string
required
Claude 模型标识,支持的模型包括:
  • claude-sonnet-4-20250514
  • claude-sonnet-4-5-20250929
  • claude-haiku-4-5-20251001
  • claude-opus-4-5-20251101(推荐替代 claude-3-opus)
  • 其他 Claude 系列模型
messages
array
required
对话消息列表,每个元素包含 role(user/assistant)和 contentcontent 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
system
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。
tools
array
工具定义列表(可选),用于计算工具调用相关的 token 数量。

响应参数

input_tokens
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)

基础示例

curl -X POST "https://console.mixroute.io/v1/messages/count_tokens" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-sonnet-4-5-20250929",
    "messages": [
      {
        "role": "user",
        "content": "Hello, how are you?"
      }
    ]
  }'

Python 示例

from anthropic import Anthropic

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

# 计算 token 数量
response = client.messages.count_tokens(
    model="claude-sonnet-4-5-20250929",
    system="You are a helpful assistant.",
    messages=[
        {"role": "user", "content": "Hello, Claude!"}
    ]
)

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

响应示例

{
  "input_tokens": 14
}

高级用例

curl -X POST "https://console.mixroute.io/v1/messages/count_tokens" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "model": "claude-sonnet-4-5-20250929",
    "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"]
        }
      }
    ]
  }'

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:
# 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-sonnet-4-5-20250929",
        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:
MAX_CONTEXT_WINDOW = 200000  # Claude Sonnet 4.5 的上下文窗口

response = client.messages.count_tokens(
    model="claude-sonnet-4-5-20250929",
    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:
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-sonnet-4-5-20250929",
        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

{
  "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

{
  "error": {
    "message": "无效的 token",
    "type": "invalid_request_error"
  }
}

相关资源

curl --request POST \
  --url https://console.mixroute.io/v1/messages/count_tokens \
  --header 'Authorization: Bearer sk-xxxxxxxxxx' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "claude-sonnet-4-5-20250929",
    "messages": [
      {"role": "user", "content": "Hello, how are you?"}
    ]
  }'
{
  "input_tokens": 14
}